Power grid fault situation quantum simulation system and method based on quantum Monte Carlo
The quantum Monte Carlo simulation system solves the problem of high computational resource and time requirements in fault analysis of large and complex power grids, and achieves efficient and accurate power grid fault assessment, especially in the handling of multiple steady-state operation modes.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-12-15
- Publication Date
- 2026-03-10
AI Technical Summary
Existing Monte Carlo simulation-based power grid fault analysis methods require significant computational resources and time to handle cascading faults in large and complex power grids, resulting in high computational costs and difficulty in effectively handling multiple steady-state operating modes of the power grid, thus reducing the accuracy of risk assessment.
A quantum simulation system for power grid fault conditions based on quantum Monte Carlo is adopted. The system acquires power grid data through a data preprocessing module, maps a simplified power grid model to quantum states through a quantum state mapping module, performs power grid fault simulation on a quantum computer through a quantum simulation calculation module, and generates a fault assessment report through a result analysis module. Quantum variational algorithms and Monte Carlo simulation algorithms are used to improve computational efficiency and accuracy.
It significantly shortens the power grid fault simulation time, saves resources, improves the accuracy of power grid reliability assessment and reduces computing costs. It can effectively handle multiple steady-state operation modes of the power grid and improve the accuracy of risk assessment.
Smart Images
Figure CN121637832A_ABST
Abstract
Description
TECHNICAL FIELD
[0001] The present application relates to the technical field of power grid fault analysis, and in particular to a power grid fault situation quantum simulation system and method based on quantum Monte Carlo. BACKGROUND
[0002] The traditional power grid fault analysis method mainly adopts a probability evaluation based on a Monte Carlo method. This method evaluates power grid reliability by statistically analyzing fault occurrence probability through multiple random simulation of power grid operation state. For example, a typical technical solution is a Monte Carlo simulation platform based on power system simulation software. The platform first establishes a power grid model, then randomly generates fault time, simulates fault process and power grid response, and finally statistically analyzes fault occurrence probability and outputs reliability evaluation. The key technical feature of this method is its random sampling mechanism and power grid simulation model based on power system equations. The workflow is: establishing a power grid model, randomly generating fault events, running power system simulation software, collecting simulation results, and statistically analyzing and evaluating reliability. However, for large-scale complex power grids, this Monte Carlo simulation method based on classical computers requires a large amount of computing resources and time when dealing with cascading fault problems of large-scale complex power grids, has high computational cost, and is difficult to effectively handle the multi-stable operation mode of the power grid, resulting in reduced accuracy of power grid risk assessment. SUMMARY
[0003] The present application provides a power grid fault situation quantum simulation system and method based on quantum Monte Carlo, which solves the technical problem that the existing power grid fault analysis method based on Monte Carlo simulation requires a large amount of computing resources and time when dealing with cascading fault problems of large-scale complex power grids, has high computational cost, and is difficult to effectively handle the multi-stable operation mode of the power grid, resulting in reduced accuracy of power grid risk assessment.
[0004] Therefore, the first aspect of the present application provides a power grid fault situation quantum simulation system, which comprises a data preprocessing module, a quantum state mapping module, a quantum simulation calculation module, and a result analysis module.
[0005] The data preprocessing module is used to obtain power grid data, perform data processing on the power grid data, and output a standardized simplified power grid model.
[0006] The quantum state mapping module is used to map the simplified power grid model to a quantum state.
[0007] The quantum simulation calculation module is used to construct a parameterized quantum circuit using a quantum variational algorithm based on the simplified power grid model of the quantum state, perform power grid fault simulation on the parameterized quantum circuit on a quantum computer using a Monte Carlo simulation algorithm, and obtain fault scenario probability distribution by measuring the quantum bit state of the parameterized quantum circuit.
[0008] The results analysis module is used to perform statistical analysis based on the probability distribution of fault scenarios and generate a power grid fault assessment report.
[0009] Optionally, the quantum simulation computing module is specifically used for:
[0010] Based on a simplified power grid model of quantum states, a parameterized quantum circuit is constructed using a variable quantum characteristic solution algorithm.
[0011] The Monte Carlo simulation algorithm is used to perform power grid fault simulation on a parameterized quantum circuit on a quantum computer, and the probability distribution of fault scenarios is obtained by measuring the qubit states of the parameterized quantum circuit.
[0012] Optionally, the data preprocessing module is specifically used for:
[0013] Acquire power grid data;
[0014] Perform data cleaning on the power grid, retaining key components and lines;
[0015] Construct an undirected graph model of the power grid based on key components and lines;
[0016] The undirected graph model of the power grid is converted into a matrix representation for quantum computing, outputting a standardized simplified power grid model.
[0017] Optionally, the quantum state mapping module is specifically used for:
[0018] The simplified power grid model maps the states of power grid elements to qubits, and uses efficient coding to minimize the number of qubits.
[0019] Optionally, the quantum simulation computing module is specifically used for:
[0020] Constructing the Hamiltonian of a simplified power grid model based on quantum states;
[0021] A parameterized quantum circuit whose output state approximates the ground state of the Hamiltonian is designed using a quantum variational algorithm.
[0022] The parameters of the parameterized quantum circuit are iteratively adjusted using the stochastic gradient descent method to minimize the expected energy of the parameterized quantum circuit output. A power grid fault simulation is then performed on the parameterized quantum circuit on a quantum computer.
[0023] By measuring the quantum states of parameterized quantum circuits during simulated power grid faults, the probability distribution of fault scenarios under different power grid conditions is obtained.
[0024] Optionally, the results analysis module is specifically used for:
[0025] According to the fault scene probability distribution, statistics are performed, the fault scene probability distribution statistical results are visually displayed in the form of a chart, and a power grid fault assessment report is generated.
[0026] The second aspect of the application provides a power grid fault situation quantum simulation method, comprising:
[0027] The data preprocessing module is used to acquire power grid data, perform data processing on the power grid data, and output a standardized simplified power grid model.
[0028] The quantum state mapping module is used to map the simplified power grid model to a quantum state.
[0029] The quantum simulation calculation module is used to construct a parameterized quantum circuit based on the quantum state simplified power grid model by using a quantum variational algorithm, perform power grid fault simulation on the parameterized quantum circuit on a quantum computer by using a Monte Carlo simulation algorithm, and obtain a fault scene probability distribution by measuring the quantum bit state of the parameterized quantum circuit.
[0030] The result analysis module is used to perform statistics according to the fault scene probability distribution, and generate a power grid fault assessment report.
[0031] Optionally, the quantum simulation calculation module is used to construct a parameterized quantum circuit based on the quantum state simplified power grid model by using a quantum variational algorithm, perform power grid fault simulation on the parameterized quantum circuit on a quantum computer by using a Monte Carlo simulation algorithm, and obtain a fault scene probability distribution by measuring the quantum bit state of the parameterized quantum circuit, comprising:
[0032] The quantum simulation calculation module is used to construct a parameterized quantum circuit based on the quantum state simplified power grid model by using a variational quantum feature solving algorithm, perform power grid fault simulation on the parameterized quantum circuit on a quantum computer by using a Monte Carlo simulation algorithm, and obtain a fault scene probability distribution by measuring the quantum bit state of the parameterized quantum circuit.
[0033] Optionally, the data preprocessing module is used to acquire power grid data, perform data processing on the power grid data, and output a standardized simplified power grid model, comprising:
[0034] The data preprocessing module is used to acquire power grid data, perform data cleaning on the power grid data, retain key elements and lines, construct a power grid undirected graph model according to the key elements and lines, convert the power grid undirected graph model into a matrix representation for quantum calculation, and output a standardized simplified power grid model.
[0035] Optionally, the quantum state mapping module is used to map the simplified power grid model to a quantum state, comprising:
[0036] The states of the power grid elements of the simplified power grid model are mapped to quantum bits by a quantum state mapping module, and the number of quantum bits is minimized by using efficient coding.
[0037] From the above technical solutions, the power grid fault situation quantum simulation system provided by the application has the following advantages:
[0038] The power grid fault situation quantum simulation system provided by the application obtains a simplified power grid model based on quantum states through data processing based on power grid data, constructs a parameterized quantum circuit by using a quantum variational algorithm based on the simplified power grid model based on quantum states, performs power grid fault simulation on the parameterized quantum circuit on a quantum computer by using a Monte Carlo simulation algorithm, obtains a fault scenario probability distribution by measuring the quantum bit states of the parameterized quantum circuit, and generates a power grid fault evaluation report by performing statistics according to the fault scenario probability distribution. The parallel computing capability of the quantum computer can significantly shorten the time of power grid fault simulation and save resources, the execution of power grid fault simulation on the quantum computer by using the variational quantum feature solving algorithm combined with the Monte Carlo simulation algorithm can more accurately simulate low-probability events, improve the accuracy of power grid reliability evaluation, and reduce the computing cost, and can effectively handle the multi-stable state operation mode of the power grid, and improve the accuracy of power grid risk evaluation. The technical problem of the existing power grid fault analysis method based on Monte Carlo simulation, which needs a large amount of computing resources and time when processing the cascading fault problem of large and complex power grids, has high computing cost, and is difficult to effectively handle the multi-stable state operation mode of the power grid, resulting in reduced accuracy of power grid risk evaluation, is solved. BRIEF DESCRIPTION OF DRAWINGS
[0039] In order to more clearly illustrate the technical solutions in the embodiments of the application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or the prior art description. Obviously, the drawings in the following description only constitute some embodiments of the application, and for those skilled in the art, other related drawings can also be obtained without creative labor on the basis of these drawings.
[0040] Figure 1 The structure diagram of the power grid fault situation quantum simulation system provided in the embodiments of the application is shown in the figure.
[0041] Figure 2 The flowchart of the power grid fault situation quantum simulation method provided in the embodiments of the application is shown in the figure. DETAILED DESCRIPTION
[0042] In order to make the person skilled in the art better understand the technical scheme of the present application, the technical scheme in the embodiments of the present application will be described clearly and completely below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, not all. Based on the embodiments in the present application, all other embodiments obtained by the person skilled in the art without creative labor are within the protection scope of the present application.
[0043] For the convenience of understanding, please refer to Figure 1 The present application provides an embodiment of a power grid fault posture quantum simulation system, comprising a data preprocessing module, a quantum state mapping module, a quantum simulation calculation module and a result analysis module.
[0044] The data preprocessing module is used for acquiring power grid data, performing data processing on the power grid data, and outputting a standardized simplified power grid model.
[0045] The quantum state mapping module is used for mapping the simplified power grid model to a quantum state.
[0046] The quantum simulation calculation module is used for constructing a parameterized quantum circuit by using a quantum variational algorithm based on the simplified power grid model of the quantum state, performing power grid fault simulation on the parameterized quantum circuit on a quantum computer by using a Monte Carlo simulation algorithm, and obtaining a fault scenario probability distribution by measuring the quantum bit state of the parameterized quantum circuit.
[0047] The result analysis module is used for performing statistics according to the fault scenario probability distribution and generating a power grid fault evaluation report.
[0048] It should be noted that the power grid fault posture quantum simulation system in the embodiments of the present application comprises a data preprocessing module, a quantum state mapping module, a quantum simulation calculation module and a result analysis module, and the data preprocessing module, the quantum state mapping module, the quantum simulation calculation module and the result analysis module are connected in sequence. The data preprocessing module acquires power grid data from a SCADA (Supervisory Control And Data Acquisition, data acquisition and monitoring control) system and power system simulation software, performs data processing on the power grid data, including data cleaning, smoothing and feature extraction, etc., retains key elements and lines, constructs a power grid undirected graph model according to the key elements and lines, the nodes of the power grid undirected graph model represent generators, transformers and other elements, the edges represent line connections, converts the power grid undirected graph model into a standardized format of matrix representation for quantum calculation, and outputs a standardized simplified power grid model.
[0049] The quantum state mapping module is configured to map the simplified power grid model to quantum states. Specifically, the states of the power grid elements of the simplified power grid model are mapped to qubits, with the normal state being 0 and the fault state being 1, and an efficient encoding is used to minimize the number of qubits.
[0050] The quantum simulation computing module is configured to perform power grid fault simulation on the quantum computer based on the quantum state-based simplified power grid model using a quantum variational algorithm, and obtain the probability distribution of the fault scenarios by measuring the quantum state of the qubits of the quantum state-based simplified power grid model. In one embodiment, the quantum variational algorithm is a variational quantum eigensolver (VQE). VQE is a hybrid quantum-classical algorithm that builds a parameterized quantum circuit to approximate the ground state of a target Hamiltonian using a quantum computer, and iteratively adjusts the circuit parameters using a classical optimizer to minimize the expected energy. The power grid state is mapped to the eigenstate of the Hamiltonian, and the low-energy state corresponds to the stable state and the high-energy state corresponds to the fault state. The core advantage of this algorithm is that it can effectively run on current noise-tolerant intermediate-scale quantum (NISQ) devices, with relatively low requirements for the number of qubits and circuit depth, and has the ability to handle complex combinatorial optimization problems. Specifically, a Hamiltonian of a quantum state-based simplified power grid model is constructed, which can reflect the stability of the power grid. The more faults in the power grid, the higher the energy value reflected by the Hamiltonian. A parameterized quantum circuit is designed to approximate the ground state of the Hamiltonian, and the output state of the parameterized quantum circuit can approximate the ground state of the Hamiltonian. The structure and number of parameters of the parameterized quantum circuit need to be adjusted according to the size and complexity of the power grid. The random gradient descent method is used to iteratively adjust the parameters of the parameterized quantum circuit to minimize the expected energy of the parameterized quantum circuit, and the parameterized quantum circuit is executed on the quantum computer to simulate power grid faults. The random gradient descent method is based on the application of Monte Carlo simulation, which approximates the expected gradient of the loss function by random sampling, thereby accelerating the convergence process. Based on the Monte Carlo simulation method, the quantum state output by the parameterized quantum circuit is measured during the simulation of power grid faults, and the parameterized quantum circuit is measured multiple times to obtain the probability distribution of the fault scenarios of different power grid states.
[0051] In one embodiment, the quantum computer is a superconducting quantum computer, and the number of qubits is determined according to the size of the power grid. The number of qubits for a medium-sized power grid is 50, and the number of qubits for a large-sized power grid is several hundred to several thousand. The quantum computer is configured with a high-performance server cluster with a 64-core CPU, 512 GB of memory, and several TB of SSD storage. Python, PSS / E, Qiskit, and other software are installed, and high-speed network connections are provided.
[0052] The result analysis module is used for statistical analysis according to the fault scenario probability distribution, identifies the most likely fault sequence and the probability of the occurrence of the cascading failure, and visually displays the statistical results of the fault scenario probability distribution in the form of a chart. The fault scenario probability distribution represents the probability of each line being faulty and the probability of the occurrence of the cascading failure. By analyzing the probability distribution, the line most prone to failure and the most likely cascading failure path can be identified. This will help the power grid operator to take preventive measures to improve the reliability of the power grid. Finally, according to the statistical analysis results of the fault scenario probability distribution, a power grid failure assessment report is generated in a preset format.
[0053] The power grid failure state quantum simulation system adopts a hierarchical architecture design. The data preprocessing module corresponds to the data preprocessing layer, the quantum state mapping module corresponds to the quantum state mapping layer, the quantum simulation calculation module corresponds to the quantum simulation calculation layer, and the result analysis module corresponds to the result post-processing layer. The layers communicate through RESTful API, exchange data in JSON format, and use MongoDB database for storage. The system is deployed in a local data center Ubuntu environment, uses parallel computing and microservice architecture, and is equipped with monitoring log function.
[0054] Taking a specific implementation scenario as an example, in the embodiment of the application, an IEEE 14-node power system (5 generators, 14 nodes, and 20 lines) is taken as an example:
[0055] Configuration parameters: 20 qubits encode 20 line states; VQE circuit with depth 3, containing Ry and Rz rotation gates; gradient descent method is used to optimize circuit parameters.
[0056] Optimization settings: Hamiltonian is designed as a penalty function, the more faults, the higher the energy; gradient descent method learning rate 0.01, iteration 1000 times.
[0057] Measurement settings: 1000 quantum circuit measurements are performed to obtain the fault probability distribution.
[0058] The operation steps and implementation process are as follows:
[0059] Power grid model construction: use Python and NetworkX library to construct the undirected graph model of IEEE 14-node system, and convert it to matrix representation suitable for quantum computing.
[0060] Quantum state mapping: map the line state in the power grid model to the state of 20 qubits.
[0061] Parameterized quantum circuit construction: use Qiskit to build a VQE circuit with depth 3 and initialize the circuit parameters.
[0062] Parameter optimization: The parameters of the VQE circuit are optimized using stochastic gradient descent, with the goal of minimizing the expected value of the objective Hamiltonian.
[0063] Quantum circuit simulation: Run the VQE circuit using a quantum simulator or a real quantum computer and perform 1000 measurements to obtain the probability distribution of line fault states.
[0064] Results Analysis: Analyze the measurement results, calculate the probability of different fault scenarios, and draw probability distribution diagrams.
[0065] The power grid fault state quantum simulation system provided by this invention processes power grid data to obtain a simplified power grid model based on quantum states. Based on this simplified model, a parameterized quantum circuit is constructed using a quantum variational algorithm. A Monte Carlo simulation algorithm is then used to perform power grid fault simulation on this parameterized quantum circuit on a quantum computer. The probability distribution of fault scenarios is obtained by measuring the qubit states of the parameterized quantum circuit. Statistical analysis is performed based on this probability distribution to generate a power grid fault assessment report. The parallel computing capability of quantum computers can significantly shorten the time for power grid fault simulation and save resources. The use of a variational quantum characteristic solving algorithm combined with Monte Carlo simulation on a quantum computer can more accurately simulate low-probability events, improving the accuracy of power grid reliability assessment and reducing computational costs. Furthermore, it can effectively handle the multi-stable operating modes of the power grid, improving the accuracy of power grid risk assessment. This system solves the technical problem that existing Monte Carlo simulation-based power grid fault analysis methods require significant computational resources and time when dealing with cascading faults in large and complex power grids, resulting in high computational costs and difficulty in effectively handling the multi-stable operating modes of the power grid, thus reducing the accuracy of power grid risk assessment.
[0066] The quantum simulation system for power grid fault conditions provided by this invention can be applied to the reliability assessment of large-scale power systems, helping power companies identify potential weaknesses and develop more effective power system maintenance and planning schemes. For example, it can be used to assess the reliability of different power system topologies, guiding power grid planning and upgrades.
[0067] For easier understanding, please refer to Figure 2 This invention provides an embodiment of a quantum simulation method for power grid fault conditions, comprising:
[0068] Step 101: Obtain power grid data through the data preprocessing module, process the power grid data, and output a standardized simplified power grid model.
[0069] Step 102: Map the simplified power grid model to quantum states using the quantum state mapping module.
[0070] Step 103: Based on a simplified power grid model of quantum states, a parameterized quantum circuit is constructed using a quantum variational algorithm through a quantum simulation computing module. A Monte Carlo simulation algorithm is then used to perform power grid fault simulation on the parameterized quantum circuit on a quantum computer. The probability distribution of fault scenarios is obtained by measuring the qubit states of the parameterized quantum circuit.
[0071] Step 104: Statistically analyze the probability distribution of fault scenarios using the results analysis module to generate a power grid fault assessment report.
[0072] In one embodiment, power grid data is acquired through a data preprocessing module, the power grid data is processed, and a standardized simplified power grid model is output, including:
[0073] The power grid data is acquired through a data preprocessing module, cleaned, and key components and lines are retained. An undirected graph model of the power grid is constructed based on the key components and lines, and then converted into a matrix representation for quantum computing, outputting a standardized simplified power grid model.
[0074] In one embodiment, mapping a simplified power grid model to quantum states via a quantum state mapping module includes:
[0075] The quantum state mapping module maps the states of power grid components to qubits in a simplified power grid model, and uses efficient coding to minimize the number of qubits.
[0076] In one embodiment, a parameterized quantum circuit is constructed using a quantum variational algorithm based on a simplified power grid model of quantum states via a quantum simulation computing module. A Monte Carlo simulation algorithm is then used to perform power grid fault simulation on the parameterized quantum circuit on a quantum computer. The probability distribution of fault scenarios is obtained by measuring the qubit states of the parameterized quantum circuit, including:
[0077] Through the quantum simulation computing module, a parameterized quantum circuit is constructed based on a simplified power grid model of quantum states using a variable quantum characteristic solution algorithm. The Monte Carlo simulation algorithm is then used to perform power grid fault simulation on the parameterized quantum circuit on a quantum computer. The probability distribution of fault scenarios is obtained by measuring the qubit states of the parameterized quantum circuit.
[0078] In one embodiment, the result analysis module performs statistical analysis based on the probability distribution of fault scenarios to generate a power grid fault assessment report, including:
[0079] The results analysis module performs statistical analysis based on the probability distribution of fault scenarios, and visualizes the statistical results of the probability distribution of fault scenarios in the form of charts, generating a power grid fault assessment report.
[0080] In one embodiment, step 103 specifically includes:
[0081] The Hamiltonian of a simplified power grid model based on quantum states is constructed using a quantum simulation computing module.
[0082] A parameterized quantum circuit with an output state approximating the ground state of the Hamiltonian is designed using a quantum variational algorithm. The parameters of the parameterized quantum circuit are iteratively adjusted using the stochastic gradient descent method to minimize the expected energy of the output of the parameterized quantum circuit. A power grid fault simulation is performed on the parameterized quantum circuit on a quantum computer. During the simulated power grid fault, the quantum state of the parameterized quantum circuit is measured to obtain the probability distribution of fault scenarios under different power grid states.
[0083] The power grid fault state quantum simulation method provided in this embodiment of the invention is applied to the power grid fault state quantum simulation system provided in this invention. Its principle is the same as that of the power grid fault state quantum simulation system provided in this invention, and will not be repeated here.
[0084] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.
[0085] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims
1. A power grid failure scenario quantum simulation system, characterized in that, The method comprises the following steps: a data preprocessing module, a quantum state mapping module, a quantum simulation calculation module, and a result analysis module; The data preprocessing module is used for acquiring power grid data, performing data processing on the power grid data, and outputting a standardized simplified power grid model; The quantum state mapping module is used for mapping the simplified power grid model to a quantum state; The quantum simulation calculation module is used for constructing a parameterized quantum circuit by using a quantum variation algorithm based on the simplified power grid model of the quantum state, performing power grid fault simulation on the parameterized quantum circuit by using a Monte Carlo simulation algorithm on a quantum computer, and obtaining a fault scenario probability distribution by measuring the quantum bit state of the parameterized quantum circuit; The result analysis module is used for performing statistics according to the fault scenario probability distribution and generating a power grid fault evaluation report.
2. The power grid failure scenario quantum simulation system of claim 1, wherein, The quantum simulation calculation module is specifically used for: constructing a parameterized quantum circuit by using a variation quantum characteristic solving algorithm based on the simplified power grid model of the quantum state; performing power grid fault simulation on the parameterized quantum circuit by using a Monte Carlo simulation algorithm on a quantum computer, and obtaining a fault scenario probability distribution by measuring the quantum bit state of the parameterized quantum circuit.
3. The power grid failure scenario quantum simulation system of claim 1, wherein, The data preprocessing module is specifically used for: acquiring power grid data; performing data cleaning on the power grid data, and retaining key elements and lines; constructing a power grid undirected graph model according to the key elements and lines; converting the power grid undirected graph model into a matrix representation for quantum calculation, and outputting a standardized simplified power grid model.
4. The power grid failure scenario quantum simulation system of claim 1, wherein, The quantum state mapping module is specifically used for: mapping the power grid element state of the simplified power grid model to a quantum bit, and minimizing the number of quantum bits by using efficient coding.
5. The power grid failure scenario quantum simulation system of claim 1, wherein, The quantum simulation calculation module is specifically used for: constructing a Hamiltonian of the simplified power grid model of the quantum state; designing a parameterized quantum circuit whose output state approximates the ground state of the Hamiltonian by using a quantum variation algorithm; iteratively adjusting the parameters of the parameterized quantum circuit by using a stochastic gradient descent method, so that the expected energy output by the parameterized quantum circuit is minimized, and performing power grid fault simulation on the parameterized quantum circuit on a quantum computer; measuring the quantum state of the parameterized quantum circuit during the simulation of the power grid fault, and obtaining a fault scenario probability distribution of different power grid states.
6. The power grid failure scenario quantum simulation system of claim 1, wherein, The result analysis module is specifically used for: performing statistics according to the fault scenario probability distribution, visually displaying the statistical results of the fault scenario probability distribution in the form of charts, and generating a power grid fault evaluation report.
7. A power grid failure scenario quantum simulation method, characterized in that, The method comprises the following steps: acquiring power grid data by using the data preprocessing module, performing data processing on the power grid data, and outputting a standardized simplified power grid model; mapping the simplified power grid model to a quantum state by using the quantum state mapping module; constructing a parameterized quantum circuit by using a quantum variation algorithm based on the simplified power grid model of the quantum state by using the quantum simulation calculation module, performing power grid fault simulation on the parameterized quantum circuit by using a Monte Carlo simulation algorithm on a quantum computer, and obtaining a fault scenario probability distribution by measuring the quantum bit state of the parameterized quantum circuit; performing statistics according to the fault scenario probability distribution by using the result analysis module, and generating a power grid fault evaluation report.
8. The power grid failure scenario quantum simulation method of claim 7, wherein, The quantum simulation calculation module is used for constructing a parameterized quantum circuit based on a simplified power grid model of quantum states by using a quantum variational algorithm, performing power grid fault simulation on the parameterized quantum circuit on a quantum computer by using a Monte Carlo simulation algorithm, and obtaining a fault scenario probability distribution by measuring quantum bit states of the parameterized quantum circuit, including: The quantum simulation calculation module is used for constructing a parameterized quantum circuit based on a simplified power grid model of quantum states by using a variational quantum feature solving algorithm, performing power grid fault simulation on the parameterized quantum circuit on a quantum computer by using a Monte Carlo simulation algorithm, and obtaining a fault scenario probability distribution by measuring quantum bit states of the parameterized quantum circuit.
9. The power grid failure scenario quantum simulation method of claim 7, wherein, The data preprocessing module is used for obtaining power grid data, performing data processing on the power grid data, and outputting a standardized simplified power grid model, including: The data preprocessing module is used for obtaining power grid data, performing data cleaning on the power grid data, retaining key components and lines, constructing a power grid undirected graph model according to the key components and lines, converting the power grid undirected graph model into a matrix representation for quantum computing, and outputting a standardized simplified power grid model.
10. The power grid failure scenario quantum simulation method of claim 7, wherein, The quantum state mapping module is used for mapping the simplified power grid model to quantum states, including: The quantum state mapping module is used for mapping power grid element states of the simplified power grid model to quantum bits, and minimizing the number of quantum bits by using efficient coding.