Joint operation method and system of power system digital real-time simulation platform

Abstract

The application discloses a kind of joint operation methods of power system digital real-time simulation platform, including obtaining the data information of target power system digital real-time simulation platform;Fiber-optic communication module is constructed and is connected high fidelity electromagnetic transient power grid simulation environment and energy storage converter cluster and control and protection hardware-in-the-loop test environment, to realize data interconnection;Interconnection interface decoupling module is constructed and is connected high fidelity electromagnetic transient power grid simulation environment and energy storage converter cluster and control and protection hardware-in-the-loop test environment, to realize the parallel access of platform and model;Complete the joint operation of target power system digital real-time simulation platform.The application also discloses a kind of systems for implementing the joint operation method of the power system digital real-time simulation platform.The application not only realizes the joint operation of power system digital real-time simulation platform, but also can realize data real-time cooperation and synchronization, with high reliability, good accuracy.

Description

Technical Field

[0001] This invention belongs to the field of electrical automation, and specifically relates to a joint operation method and system for a digital real-time simulation platform for power systems. Background Technology

[0002] With economic and technological development and the improvement of people's living standards, electricity has become an indispensable secondary energy source in people's production and daily life, bringing endless convenience. Therefore, ensuring a stable and reliable supply of electricity has become one of the most important tasks of the power system.

[0003] Currently, an increasing number of new energy power generation systems are being integrated into the power grid and generating electricity. The randomness and intermittency of the output of these new energy power generation systems have placed enormous pressure on the safe and stable operation of the power system. Therefore, the power system has begun to use digital real-time simulation platforms to simulate and verify grid planning, operation analysis, and control strategies.

[0004] Currently, digital real-time simulation platforms for power systems construct a high-fidelity electromagnetic transient power grid simulation environment through a grid-level real-time simulation platform, and simultaneously construct an energy storage converter cluster and control and protection hardware-in-the-loop (HIL) test environment through an equipment-level real-time simulation system. The operation of the digital real-time simulation platform is achieved through data interaction between these two systems, thus enabling simulation verification. However, existing joint operation schemes for power system digital real-time simulation platforms suffer from poor data interaction and synchronization, making it difficult to support collaborative simulation across multiple time scales. Summary of the Invention

[0005] One of the objectives of this invention is to provide a joint operation method for a power system digital real-time simulation platform that can achieve real-time data collaboration and synchronization, and has high reliability and accuracy.

[0006] The second objective of this invention is to provide a system for implementing the joint operation method of the aforementioned power system digital real-time simulation platform.

[0007] The method for jointly operating the digital real-time simulation platform for power systems provided by this invention includes the following steps:

[0008] S1. Obtain data information from the target power system digital real-time simulation platform;

[0009] S2. Based on the data information obtained in step S1, construct an optical fiber communication module and connect it to the high-fidelity electromagnetic transient power grid simulation environment and the energy storage converter cluster and control and protection hardware-in-the-loop test environment to achieve data interconnection;

[0010] S3. Based on the data information obtained in step S1, construct an interconnection interface decoupling module and connect it to the high-fidelity electromagnetic transient power grid simulation environment, the energy storage converter cluster, and the control and protection hardware-in-the-loop test environment to achieve parallel access of the platform and the model;

[0011] S4. Complete the joint operation of the target power system digital real-time simulation platform.

[0012] Step S1, which involves acquiring data information from the target power system digital real-time simulation platform, specifically includes the following steps:

[0013] Acquire data information from the target power system's digital real-time simulation platform;

[0014] The data information includes communication protocol data information and simulated power consumption data information;

[0015] The simulated power data includes voltage information, current information, active power information, static power information, and frequency information.

[0016] Step S2, which involves constructing an optical fiber communication module based on the data information obtained in step S1 and connecting it to the high-fidelity electromagnetic transient power grid simulation environment, the energy storage converter cluster, and the control and protection hardware-in-the-loop test environment to achieve data interconnection, specifically includes the following steps:

[0017] Build an optical fiber communication module based on the Aurora protocol;

[0018] The fiber optic communication module is deployed on both the high-fidelity electromagnetic transient power grid simulation environment and the energy storage converter cluster and control and protection hardware-in-the-loop test environment. This reduces the communication complexity between the high-fidelity electromagnetic transient power grid simulation environment and the energy storage converter cluster and control and protection hardware-in-the-loop test environment, and improves the stability and reliability of the communication link.

[0019] The constructed fiber optic communication module includes the following components:

[0020] The constructed fiber optic communication module includes a data packet transmission submodule, a data reception and parsing submodule, an Aurora link submodule, a high-speed transceiver and fiber optic interface submodule, and a link status monitoring and anomaly handling submodule.

[0021] The data packaging and sending submodule is used to obtain the variables to be exchanged from the local simulation model or the decoupling function module of the interconnection interface, and to complete the standardization of data dimensions and data types, field mapping and frame assembly.

[0022] The data receiving and parsing submodule is used to unpack, restore fields, and check the validity of data frames sent by the peer, and output them to the simulation model or interconnection interface decoupling function module on the local end.

[0023] The Aurora link submodule uses Aurora 8B and 10B control characters to achieve frame boundary identification and link alignment.

[0024] The high-speed transceiver and fiber optic interface submodule achieves point-to-point electrical isolation between the serial transceiver and the fiber optic medium, and supports bandwidth enhancement by expanding the number of channels or isolated transmission according to data stream.

[0025] The link status monitoring and anomaly handling submodule monitors and records link establishment status, frame loss and frame errors, frame sequence number continuity, buffer queue level, and timeout events. When an anomaly occurs, it triggers a degradation strategy, including maintaining the previous valid value, limiting and blocking, or switching to a safe mode, to avoid uncontrollable delays and ensure the stable operation of the co-simulation closed loop. The anomalies include verification failure, alignment anomaly, and reception timeout.

[0026] Step S3, which involves constructing an interconnection interface decoupling module based on the data information obtained in step S1 and connecting it to the high-fidelity electromagnetic transient power grid simulation environment, the energy storage converter cluster, and the control and protection hardware-in-the-loop test environment, to achieve parallel access of the platform and the model, specifically includes the following steps:

[0027] The constructed interconnection interface decoupling module is used to support model decomposition and parallel solution in the collaborative simulation process between the high-fidelity electromagnetic transient power grid simulation environment and the energy storage converter cluster and control and protection hardware in the loop test environment.

[0028] Based on traveling wave theory, combined with the equivalent form of StubLine, and an adaptive time alignment mechanism, an interconnect interface decoupling module is constructed.

[0029] The constructed interconnect interface decoupling module includes the following:

[0030] The purpose of the interconnect interface decoupling module is to establish a physically consistent and time-capable coupling interface at the decoupling boundary, so that the data exchanged across platforms meets the computational causality and energy consistency requirements of electromagnetic transient simulation, thereby reducing communication latency and non-physical phenomena caused by step misalignment.

[0031] Based on traveling wave theory, the actual cable at the split boundary is equivalent to a transmission line model characterized by distributed parameters inductance and capacitance. Propagation delay and characteristic impedance are introduced at the interface to transform the split boundary into a dynamic boundary condition with clear physical meaning.

[0032] In practice, the decomposition boundary of the high-fidelity electromagnetic transient power grid simulation environment and the energy storage converter cluster and control and protection hardware-in-the-loop test environment is equivalent to having characteristic impedance. StubLine transmission line interface: Boundary voltages are defined on both sides of the split point. and Boundary current and At the same time, their respective characteristic impedances are connected in series. and add equivalent incentive sources and The equivalent excitation source is used to characterize the propagation and reflection effects of traveling waves in the transmission line. The boundary quantity at the other end is mapped to the equivalent excitation source that can be calculated at this end through the propagation delay. This allows each subsystem to complete the independent solution by relying only on the historical quantity at the other end under discrete pacing and to maintain a physically consistent coupling relationship, thereby improving the ability of cross-platform joint simulation to characterize transient processes and the overall stability.

[0033] The coupling relationship on both sides of the split point is described using the StubLine equivalent form, which maps the historical voltage and current at the other end to the equivalent excitation source at this end, as follows:

[0034] In the formula, t is the current simulation time. For the equivalent propagation delay of the interface, To split the boundary k side at Voltage at any given moment; To split the boundary k side at Current at any given moment; To split the boundary m side at Voltage at any given moment; To split the boundary m side at Current at any given moment; The equivalent line resistance parameter of the interface; This represents the weighting coefficient composed of characteristic impedance and loss terms;

[0035] By constructing equivalent excitation sources, the decomposed boundary can achieve dynamic coupling of computation under discrete stepping, enabling the two sub-models to complete parallel solution without introducing algebraic loops and maintaining the stability of boundary interaction.

[0036] Construction of an adaptive time alignment mechanism:

[0037] The calculation step size for fine-step simulation of the target power system digital real-time simulation platform is set as follows: The calculation step size for coarse step size simulation is: And satisfy N is the ratio of the number of steps between the coarse step size and the fine step size;

[0038] Set the step-time alignment factor to , ;

[0039] Then the k-th coarse step time The corresponding fine step size side actual alignment time Represented as ;in It is an unknown quantity;

[0040] Therefore, the problem of exchanging interface variables across step sizes is transformed into time alignment coefficients. The problem to be solved;

[0041] Constructing input feature vectors for ,in Let m be the state vectors of the most recent m time steps on the fine step size side. Let m be the state vectors of the most recent m time steps on the coarse step size side. This represents the interface error from the previous moment. This refers to the rate of change of state and the characteristics of external disturbances;

[0042] Constructing state vectors for ,in For voltage, For current, Active power Reactive power For frequency;

[0043] Constructing time alignment coefficients The predictive mapping model is expressed as ;in, For the predicted time alignment coefficient, The parameter is The prediction model; the prediction model adopts a multilayer perceptron model or a temporal neural network model;

[0044] The prediction mapping model is trained using the following loss function:

[0045] In the formula The value of the loss function; The weight of the alignment coefficient error term is set; This is the alignment coefficient error term; Weights for the interface variable error terms; For interface variable error; The weights of the set smoothing constraint terms; For smoothing constraint terms; Weights for the defined physical consistency constraints; This is a physical consistency constraint. This represents the number of training samples; The prediction time alignment coefficient is the output of the prediction mapping model at the k-th time step. This represents the theoretical value of the time alignment coefficient at the k-th time moment. This represents the state vector corresponding to the fine step size side at the prediction alignment time; This is the state vector corresponding to the coarse step size side at the current time. Represents the square of the L2 norm; The active power in the state vector at time k; The voltage in the state vector at time k; The current in the state vector at time k;

[0046] Constructing interface error function for ,in Candidate time alignment coefficient; For vector norm; through discrete sets The search is performed to obtain the theoretical value of the time alignment coefficient at the k-th time. for ;

[0047] Calculate the time alignment coefficient after fusion. for ,in For the set prediction weights, The theoretical weights are set.

[0048] The smoothing process is performed again to calculate the final time alignment coefficient. for ,in For the set historical weights, The set fusion weights;

[0049] Calculate the interface variables used for cross-device exchange after time mapping. for ;

[0050] By constructing an adaptive time alignment mechanism, it is possible to reduce error accumulation and interface oscillation caused by time mismatch while ensuring the accuracy of interface variable mapping, thereby improving the real-time performance, stability, and physical consistency of heterogeneous simulation systems during cross-step interconnection.

[0051] This invention also provides a system for implementing the joint operation method of the power system digital real-time simulation platform, comprising a data acquisition module, a communication construction module, an interface construction module, and a joint operation module; the data acquisition module, communication construction module, interface construction module, and joint operation module are connected in series; the data acquisition module is used to acquire data information from the target power system digital real-time simulation platform and upload the data information to the communication construction module; the communication construction module is used to construct an optical fiber communication module based on the received data information and the acquired data information, and connect the high-fidelity electromagnetic transient power grid simulation environment and the energy storage converter cluster and control and protection hardware-in-the-loop test environment to achieve data interconnection, and upload the data information to the interface construction module; the interface construction module is used to construct an interconnection interface decoupling module based on the received data information and the acquired data information, and connect the high-fidelity electromagnetic transient power grid simulation environment and the energy storage converter cluster and control and protection hardware-in-the-loop test environment to achieve parallel access of the platform and the model, and upload the data information to the joint operation module; the joint operation module is used to complete the joint operation of the target power system digital real-time simulation platform based on the received data information.

[0052] The method and system for joint operation of the digital real-time simulation platform for power systems provided by this invention, through the construction and application of optical fiber communication modules and interconnection interface decoupling modules, not only realizes the joint operation of the digital real-time simulation platform for power systems, but also enables real-time data collaboration and synchronization, with high reliability and good accuracy. Attached Figure Description

[0053] Figure 1 This is a schematic diagram of the method flow of the present invention.

[0054] Figure 2 This is a schematic diagram of the StubLine transmission line interface of the method of the present invention.

[0055] Figure 3 This is a schematic diagram of the delay test results of an embodiment of the method of the present invention.

[0056] Figure 4 This is a schematic diagram of the test results of an embodiment of the method of the present invention.

[0057] Figure 5 This is a schematic diagram of the functional modules of the system of the present invention. Detailed Implementation

[0058] like Figure 1 The diagram shown is a flowchart of the method of the present invention: The joint operation method of this power system digital real-time simulation platform disclosed in the present invention includes the following steps:

[0059] S1. Obtain data information from the target power system digital real-time simulation platform; specifically including the following steps:

[0060] Acquire data information from the target power system's digital real-time simulation platform;

[0061] The data information includes communication protocol data information and simulated power consumption data information;

[0062] The simulated power data includes voltage information, current information, active power information, static power information, and frequency information;

[0063] S2. Based on the data obtained in step S1, construct an optical fiber communication module and connect it to the high-fidelity electromagnetic transient power grid simulation environment, the energy storage converter cluster, and the control and protection hardware-in-the-loop test environment to achieve data interconnection; specifically, this includes the following steps:

[0064] Build an optical fiber communication module based on the Aurora protocol;

[0065] The fiber optic communication module is deployed on both the high-fidelity electromagnetic transient power grid simulation environment and the energy storage converter cluster and control and protection hardware loop-in test environment to reduce the communication complexity between the high-fidelity electromagnetic transient power grid simulation environment and the energy storage converter cluster and control and protection hardware loop-in test environment, and to improve the stability and reliability of the communication link.

[0066] In practical implementation, the constructed fiber optic communication module includes the following components:

[0067] The fiber optic communication module uses the Xilinx Aurora 8B 10B IP core as the core of the link layer protocol. By utilizing its standardized link layer implementation that is transparent to the physical layer, upper-layer applications do not need to deal with the details of underlying encoding, alignment, link establishment and maintenance to drive the high-speed serial transceiver to complete continuous transmission, thereby reducing implementation complexity and improving link stability and determinism.

[0068] The constructed fiber optic communication module includes a data packet transmission submodule, a data reception and parsing submodule, an Aurora link submodule, a high-speed transceiver and fiber optic interface submodule, and a link status monitoring and anomaly handling submodule.

[0069] The data packaging and sending submodule is used to obtain the variables to be exchanged from the local simulation model or the decoupling function module of the interconnection interface, and to complete the standardization of data dimensions and data types, field mapping and frame assembly.

[0070] The data receiving and parsing submodule is used to unpack, restore fields, and check the validity of data frames sent by the peer, and output them to the simulation model or interconnection interface decoupling function module on the local end.

[0071] The Aurora link submodule uses Aurora 8B 10B control characters to achieve frame boundary identification and link alignment. A typical transmission frame consists of start control characters SCP1 and SCP2, a customizable data area Data Byte 0 to Data Byte n, and end control characters ECP1 and ECP2. The data area is used to carry interactive quantities such as grid connection point voltage, current, power, status words, and control commands, and can optionally carry step counts or time markers to support cross-platform step consistency and result traceability.

[0072] The high-speed transceiver and fiber optic interface submodule achieves point-to-point electrical isolation between the serial transceiver and the fiber optic medium, and supports bandwidth enhancement by expanding the number of channels or isolated transmission according to data stream.

[0073] The link status monitoring and anomaly handling submodule monitors and records link establishment status, frame loss and frame errors, frame sequence number continuity, buffer queue level, and timeout events. When an anomaly occurs, it triggers a degradation strategy, including maintaining the previous valid value, limiting and blocking, or switching to a safe mode, to avoid uncontrollable latency and ensure the stable operation of the co-simulation closed loop. The anomalies include verification failure, alignment anomaly, and reception timeout.

[0074] S3. Based on the data obtained in step S1, construct an interconnection interface decoupling module and connect it to the high-fidelity electromagnetic transient power grid simulation environment, the energy storage converter cluster, and the control and protection hardware-in-the-loop test environment to achieve parallel access of the platform and the model; specifically, this includes the following steps:

[0075] The constructed interconnection interface decoupling module is used to support model decomposition and parallel solution in the collaborative simulation process between the high-fidelity electromagnetic transient power grid simulation environment and the energy storage converter cluster and control and protection hardware in the loop test environment. Its purpose is to establish a physically consistent and time-realizable coupling interface at the decomposition boundary, so that the voltage and current quantities exchanged across platforms meet the computational causality and energy consistency requirements of electromagnetic transient simulation, thereby reducing non-physical phenomena such as phase jumps, power imbalances and numerical oscillations caused by communication delays and step misalignments.

[0076] Based on traveling wave theory, combined with the equivalent form of StubLine, and an adaptive time alignment mechanism, an interconnect interface decoupling module is constructed.

[0077] In practical implementation, the interconnection interface decoupling module includes the following:

[0078] The purpose of the interconnect interface decoupling module is to establish a physically consistent and time-capable coupling interface at the decoupling boundary, so that the data exchanged across platforms meets the computational causality and energy consistency requirements of electromagnetic transient simulation, thereby reducing communication latency and non-physical phenomena caused by step misalignment.

[0079] Based on traveling wave theory, the actual cable at the split boundary is equivalent to a transmission line model characterized by distributed parameters inductance and capacitance. Propagation delay and characteristic impedance are introduced at the interface to transform the split boundary into a dynamic boundary condition with clear physical meaning.

[0080] In practice, the decomposition boundary of the high-fidelity electromagnetic transient power grid simulation environment and the energy storage converter cluster and control and protection hardware-in-the-loop test environment is equivalent to having characteristic impedance. StubLine transmission line interface (structure as follows) Figure 2 As shown): Boundary voltages are defined on both sides of the split point. and Boundary current and At the same time, their respective characteristic impedances are connected in series. and add equivalent incentive sources and The equivalent excitation source is used to characterize the propagation and reflection effects of traveling waves in the transmission line. The boundary quantity at the other end is mapped to the equivalent excitation source that can be calculated at this end through the propagation delay. This allows each subsystem to complete the independent solution by relying only on the historical quantity at the other end under discrete pacing and to maintain a physically consistent coupling relationship, thereby improving the ability of cross-platform joint simulation to characterize transient processes and the overall stability.

[0081] The coupling relationship on both sides of the split point is described using the StubLine equivalent form, which maps the historical voltage and current at the other end to the equivalent excitation source at this end, as follows:

[0082] In the formula, t is the current simulation time. For the equivalent propagation delay of the interface, To split the boundary k side at Voltage at any given moment; To split the boundary k side at Current at any given moment; To split the boundary m side at Voltage at any given moment; To split the boundary m side at Current at any given moment; The equivalent line resistance parameter of the interface; This represents the weighting coefficient composed of characteristic impedance and loss terms;

[0083] By constructing equivalent excitation sources, the decomposed boundary can achieve dynamic coupling of computation under discrete stepping, enabling the two sub-models to complete parallel solution without introducing algebraic loops and maintaining the stability of boundary interaction.

[0084] In addition, the traveling wave interface has matching constraints on propagation delay, simulation step size, and data exchange cycle between platforms. The propagation delay needs to form an achievable timing relationship with the discrete step size to ensure the stable operation of the interface under real-time parallel conditions. For cases where the propagation delay is insufficient due to the short physical line, the interface can meet the conditions for step alignment and stable interaction by setting an equivalent delay or adjusting the interface parameter configuration.

[0085] Construction of an adaptive time alignment mechanism:

[0086] The calculation step size for fine-step simulation of the target power system digital real-time simulation platform is set as follows: The calculation step size for coarse step size simulation is: And satisfy N is the ratio of the number of steps between the coarse step size and the fine step size;

[0087] Set the step-time alignment factor to , ;

[0088] Then the k-th coarse step time The corresponding fine step size side actual alignment time Represented as ;in It is an unknown quantity;

[0089] Therefore, the problem of exchanging interface variables across step sizes is transformed into time alignment coefficients. The problem to be solved;

[0090] Considering that the time alignment result is related not only to the current state but also to the evolution of the preceding state, the accumulation of interface errors, and the characteristics of perturbation changes, the historical state information of the fine-step side and the coarse-step side, the interface error of the previous time step, and the perturbation characteristics are jointly constructed as the model input; and the input feature vector is constructed. for ,in Let m be the state vectors of the most recent m time steps on the fine step size side. Let m be the state vectors of the most recent m time steps on the coarse step size side. This represents the interface error from the previous moment. This refers to the rate of change of state and the characteristics of external disturbances;

[0091] Constructing state vectors for ,in For voltage, For current, Active power Reactive power For frequency;

[0092] Constructing time alignment coefficients The predictive mapping model is expressed as ;in, For the predicted time alignment coefficient, The parameter is The prediction model; the prediction model adopts a multilayer perceptron model or a temporal neural network model;

[0093] To ensure that the output of the learning model simultaneously meets the requirements of high alignment accuracy, small interface error, smooth change, and reasonable physical relationship, the following loss function is used to train the prediction mapping model:

[0094] In the formula The value of the loss function; The weight of the alignment coefficient error term is set; This is the alignment coefficient error term, which measures the magnitude of the deviation between the predicted result and the optimal alignment result. Weights for the interface variable error terms; For interface variable error, this term is used to measure the mapping error between the interface states of the fine step size side and the coarse step size side at the time of prediction alignment. The weights of the set smoothing constraint terms; As a smoothing constraint term, this term is used to suppress drastic fluctuations in prediction results between adjacent time points, and improve the continuity and stability of the time alignment coefficient output; Weights for the defined physical consistency constraints; This is a physical consistency constraint term, which is used to constrain the model output to meet basic electrical and physical relationships, thereby enhancing the physical consistency and engineering rationality of the time alignment results; This represents the number of training samples; The prediction time alignment coefficient is the output of the prediction mapping model at the k-th time step. This represents the theoretical value of the time alignment coefficient at the k-th time moment. This represents the state vector corresponding to the fine step size side at the prediction alignment time; This is the state vector corresponding to the coarse step size side at the current time. Represents the square of the L2 norm; The active power in the state vector at time k; The voltage in the state vector at time k; The current in the state vector at time k;

[0095] Considering that the learning model may exhibit prediction bias under complex operating conditions, sudden disturbances, or insufficient sample coverage, an error-driven time alignment correction mechanism is further introduced; an interface error function is constructed. for ,in Candidate time alignment coefficient; For vector norm; through discrete sets The search is performed to obtain the theoretical value of the time alignment coefficient at the k-th time. for This process is equivalent to making online corrections to the predictions given by the learning model, thereby enhancing the mechanism's adaptability under complex operating conditions.

[0096] To balance the predictive power of the learning results with the accuracy of the error correction results, the two are further fused to calculate the fused time alignment coefficient. for ,in For the set prediction weights, The theoretical weights are set.

[0097] Considering that the merged time alignment coefficient may still have local fluctuations between consecutive moments, a smoothing process is further introduced to improve the continuity of the interface mapping process and the stability of coupled operation; a second smoothing process is then performed to calculate the final time alignment coefficient. for ,in For the set historical weights, The set fusion weights;

[0098] Calculate the interface variables used for cross-device exchange after time mapping. for ;

[0099] By constructing an adaptive time alignment mechanism, it is possible to reduce error accumulation and interface oscillation caused by time mismatch while ensuring the accuracy of interface variable mapping, thereby improving the real-time performance, stability and physical consistency of heterogeneous simulation systems during cross-step interconnection.

[0100] S4. Complete the joint operation of the target power system digital real-time simulation platform.

[0101] The effects of the method of the present invention will be illustrated below with reference to an embodiment:

[0102] First, conduct transmission tests on each platform to obtain communication latency. Figure 3 As shown: Figure 3 (a) shows the curves for the system-level simulation equipment. Figure 3 (b) shows the curves for the device-level simulation equipment; it can be observed that the system-level simulation platform has a delay of 2 steps, while the device-level simulation platform has a delay of 3 steps. Therefore, without intervention, it is difficult for the two platforms to achieve joint real-time simulation.

[0103] Furthermore, joint simulation tests were conducted using two simulation platforms based on the scheme of this invention. The test group adopted a split model approach, placing an ideal voltage source and line impedance in the system-level simulation platform, and an RLC load in the equipment-level simulation platform. The two platforms were connected via a split interface. The test results are as follows: Figure 4 As shown, the voltage and current amplitudes and phases are basically consistent before and after the split, verifying the effectiveness of the present invention.

[0104] This invention constructs a cross-platform joint operation scheme that coordinates the work of an optical fiber communication module and an interconnect interface decoupling function module. Firstly, the optical fiber communication module uses a point-to-point high-speed optical fiber link based on the Aurora protocol to achieve cross-platform data exchange. Through a unified data item list, field order, encoding rules, and frame structure solidification mechanism, it ensures consistent interpretation and stable transmission of the exchanged data across both platforms. Simultaneously, it introduces a link status monitoring and anomaly degradation handling mechanism for real-time closed-loop operation to suppress the impact of frame loss, frame errors, timeouts, and other anomalies on the stability of the joint simulation. Secondly, the interconnect interface decoupling function module, based on traveling wave theory, equates the cable or line at the decoupling boundary to a StubLine transmission line interface, explicitly introducing characteristic impedance and propagation delay. It achieves causal parallel solution by constructing equivalent excitations at the local end using historical quantities from the other end, thereby transforming the cross-platform boundary from ideal algebraic coupling into physically consistent dynamic boundary conditions.

[0105] like Figure 5The diagram shows the functional modules of the system of the present invention: The system disclosed in this invention for implementing the joint operation method of the digital real-time simulation platform of the power system includes a data acquisition module, a communication construction module, an interface construction module, and a joint operation module; the data acquisition module, communication construction module, interface construction module, and joint operation module are connected in series; the data acquisition module is used to acquire data information of the target digital real-time simulation platform of the power system and upload the data information to the communication construction module; the communication construction module is used to construct an optical fiber communication module based on the received data information and the acquired data information and connect the high-fidelity electromagnetic transient power grid simulation environment and the energy storage converter cluster and control and protection hardware-in-the-loop test environment to achieve data interconnection, and upload the data information to the interface construction module; the interface construction module is used to construct an interconnection interface decoupling module based on the received data information and the acquired data information and connect the high-fidelity electromagnetic transient power grid simulation environment and the energy storage converter cluster and control and protection hardware-in-the-loop test environment to achieve parallel access of the platform and the model, and upload the data information to the joint operation module; the joint operation module is used to complete the joint operation of the target digital real-time simulation platform of the power system based on the received data information.

Claims

1. A method for joint operation of a digital real-time simulation platform for a power system, comprising the following steps: S1. Obtain data information from the target power system digital real-time simulation platform; S2. Based on the data information obtained in step S1, construct an optical fiber communication module and connect it to the high-fidelity electromagnetic transient power grid simulation environment and the energy storage converter cluster and control and protection hardware-in-the-loop test environment to achieve data interconnection; S3. Based on the data information obtained in step S1, construct an interconnection interface decoupling module and connect it to the high-fidelity electromagnetic transient power grid simulation environment, the energy storage converter cluster, and the control and protection hardware-in-the-loop test environment to achieve parallel access of the platform and the model; S4. Complete the joint operation of the target power system digital real-time simulation platform.

2. The joint operation method of the power system digital real-time simulation platform according to claim 1, characterized in that... Step S1, which involves acquiring data information from the target power system digital real-time simulation platform, specifically includes the following steps: Acquire data information from the target power system's digital real-time simulation platform; The data information includes communication protocol data information and simulated power consumption data information; The simulated power data includes voltage information, current information, active power information, static power information, and frequency information.

3. The joint operation method of the power system digital real-time simulation platform according to claim 2, characterized in that... Step S2, which involves constructing an optical fiber communication module based on the data information obtained in step S1 and connecting it to the high-fidelity electromagnetic transient power grid simulation environment, the energy storage converter cluster, and the control and protection hardware-in-the-loop test environment to achieve data interconnection, specifically includes the following steps: Build an optical fiber communication module based on the Aurora protocol; The fiber optic communication module is deployed on both the high-fidelity electromagnetic transient power grid simulation environment and the energy storage converter cluster and control and protection hardware-in-the-loop test environment. This reduces the communication complexity between the high-fidelity electromagnetic transient power grid simulation environment and the energy storage converter cluster and control and protection hardware-in-the-loop test environment, and improves the stability and reliability of the communication link.

4. The joint operation method of the power system digital real-time simulation platform according to claim 3, characterized in that... The constructed fiber optic communication module includes the following components: The constructed fiber optic communication module includes a data packet transmission submodule, a data reception and parsing submodule, an Aurora link submodule, a high-speed transceiver and fiber optic interface submodule, and a link status monitoring and anomaly handling submodule. The data packaging and sending submodule is used to obtain the variables to be exchanged from the local simulation model or the decoupling function module of the interconnection interface, and to complete the standardization of data dimensions and data types, field mapping and frame assembly. The data receiving and parsing submodule is used to unpack, restore fields, and check the validity of data frames sent by the peer, and output them to the simulation model or interconnection interface decoupling function module on the local end. The Aurora link submodule uses Aurora 8B and 10B control characters to achieve frame boundary identification and link alignment. The high-speed transceiver and fiber optic interface submodule achieves point-to-point electrical isolation between the serial transceiver and the fiber optic medium, and supports bandwidth enhancement by expanding the number of channels or isolated transmission according to data stream. The link status monitoring and anomaly handling submodule monitors and records link establishment status, frame loss and frame errors, frame sequence number continuity, buffer queue level, and timeout events. When an anomaly occurs, it triggers a degradation strategy, including maintaining the previous valid value, limiting and blocking, or switching to a safe mode, to avoid uncontrollable delays and ensure the stable operation of the co-simulation closed loop. The anomalies include verification failure, alignment anomaly, and reception timeout.

5. The joint operation method of the power system digital real-time simulation platform according to claim 4, characterized in that... Step S3, which involves constructing an interconnection interface decoupling module based on the data information obtained in step S1 and connecting it to the high-fidelity electromagnetic transient power grid simulation environment and the energy storage converter cluster and control and protection hardware-in-the-loop test environment, to achieve parallel access of the platform and the model, specifically includes the following steps: The constructed interconnection interface decoupling module is used to support model decomposition and parallel solution in the collaborative simulation process between the high-fidelity electromagnetic transient power grid simulation environment and the energy storage converter cluster and control and protection hardware in the loop test environment. Based on traveling wave theory, combined with the equivalent form of StubLine, and an adaptive time alignment mechanism, an interconnect interface decoupling module is constructed.

6. The joint operation method of the power system digital real-time simulation platform according to claim 5, characterized in that... The constructed interconnect interface decoupling module includes the following: The purpose of the interconnect interface decoupling module is to establish a physically consistent and time-capable coupling interface at the decoupling boundary, so that the data exchanged across platforms meets the computational causality and energy consistency requirements of electromagnetic transient simulation, thereby reducing communication latency and non-physical phenomena caused by step misalignment; Based on traveling wave theory, the actual cable at the split boundary is equivalent to a transmission line model characterized by distributed parameters inductance and capacitance. Propagation delay and characteristic impedance are introduced at the interface to transform the split boundary into a dynamic boundary condition with clear physical meaning. In practice, the decomposition boundary of the high-fidelity electromagnetic transient power grid simulation environment and the energy storage converter cluster and control and protection hardware-in-the-loop test environment is equivalent to having characteristic impedance. StubLine transmission line interface: Boundary voltages are defined on both sides of the split point. and Boundary current and At the same time, their respective characteristic impedances are connected in series. and add equivalent incentive sources and The equivalent excitation source is used to characterize the propagation and reflection effects of traveling waves in the transmission line. The boundary quantity at the other end is mapped to the equivalent excitation source that can be calculated at this end through the propagation delay. This allows each subsystem to complete the independent solution by relying only on the historical quantity at the other end under discrete pacing and to maintain a physically consistent coupling relationship, thereby improving the ability of cross-platform joint simulation to characterize transient processes and the overall stability. The coupling relationship on both sides of the split point is described using the StubLine equivalent form, which maps the historical voltage and current at the other end to the equivalent excitation source at this end, as follows: In the formula, t is the current simulation time. For the equivalent propagation delay of the interface, To split the boundary k side at Voltage at any given moment; To split the boundary k side at Current at any given moment; To split the boundary m side at Voltage at any given moment; To split the boundary m side at Current at any given moment; The equivalent line resistance parameter of the interface; This represents the weighting coefficient composed of characteristic impedance and loss terms; By constructing equivalent excitation sources, the decomposed boundary can achieve dynamic coupling of computation under discrete stepping, enabling the two sub-models to complete parallel solution without introducing algebraic loops and maintaining the stability of boundary interaction. Construction of an adaptive time alignment mechanism: The calculation step size for fine-step simulation of the target power system digital real-time simulation platform is set as follows: The calculation step size for coarse step size simulation is: And satisfy N is the ratio of the number of steps between the coarse step size and the fine step size; Set the step-time alignment factor to , ; Then the k-th coarse step time The corresponding fine step size side actual alignment time Represented as ;in It is an unknown quantity; Therefore, the problem of exchanging interface variables across step sizes is transformed into time alignment coefficients. The problem to be solved; Constructing input feature vectors for ,in Let m be the state vectors of the most recent m time steps on the fine step size side. Let m be the state vectors of the most recent m time steps on the coarse step size side. This represents the interface error from the previous moment. This refers to the rate of change of state and characteristics of external disturbances; Constructing state vectors for ,in For voltage, For current, Active power Reactive power For frequency; Constructing time alignment coefficients The predictive mapping model is expressed as ;in, For the predicted time alignment coefficient, The parameter is The prediction model; the prediction model adopts a multilayer perceptron model or a temporal neural network model; The prediction mapping model is trained using the following loss function: In the formula The value of the loss function; The weight of the alignment coefficient error term is set; This is the alignment coefficient error term; Weights for the interface variable error terms; For interface variable error; The weights of the set smoothing constraint terms; For smoothing constraint terms; Weights for the defined physical consistency constraints; This is a physical consistency constraint term; This represents the number of training samples; The prediction time alignment coefficient is the output of the prediction mapping model at the k-th time step. This represents the theoretical value of the time alignment coefficient at the k-th time moment. This represents the state vector corresponding to the fine step size side at the prediction alignment time; This is the state vector corresponding to the coarse step size side at the current time. Represents the square of the L2 norm; The active power in the state vector at time k; The voltage in the state vector at time k; The current in the state vector at time k; Constructing interface error function for ,in Candidate time alignment coefficient; It is a vector norm; through discrete sets The search is performed to obtain the theoretical value of the time alignment coefficient at the k-th time. for ; Calculate the time alignment coefficient after fusion. for ,in For the set prediction weights, The theoretical weights are set. The smoothing process is performed again to calculate the final time alignment coefficient. for ,in For the set historical weights, The set fusion weights; Calculate the interface variables used for cross-device exchange after time mapping. for ; By constructing an adaptive time alignment mechanism, it is possible to reduce error accumulation and interface oscillation caused by time mismatch while ensuring the accuracy of interface variable mapping, thereby improving the real-time performance, stability, and physical consistency of heterogeneous simulation systems during cross-step interconnection.

7. A system for implementing the joint operation method of the power system digital real-time simulation platform according to any one of claims 1 to 6, characterized in that... It includes a data acquisition module, a communication construction module, an interface construction module, and a joint operation module; the data acquisition module, communication construction module, interface construction module, and joint operation module are connected in series; the data acquisition module is used to acquire data information from the target power system digital real-time simulation platform and upload the data information to the communication construction module; The communication construction module is used to build an optical fiber communication module based on the received and acquired data information, and connect it to the high-fidelity electromagnetic transient power grid simulation environment and the energy storage converter cluster and control and protection hardware-in-the-loop test environment to achieve data interconnection, and upload the data information to the interface construction module; the interface construction module is used to build an interconnection interface decoupling module based on the received and acquired data information, and connect it to the high-fidelity electromagnetic transient power grid simulation environment and the energy storage converter cluster and control and protection hardware-in-the-loop test environment to achieve parallel access of the platform and model, and upload the data information to the joint operation module; The joint operation module is used to complete the joint operation of the target power system digital real-time simulation platform based on the received data information.

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