Commutation failure suppression method and device based on static security boundary and predictive control

Abstract

The application provides a commutation failure suppression method and device based on a static security boundary and predictive control, and belongs to the technical field of power system control. The method comprises the following steps: acquiring an AC commutation voltage of a high-voltage direct-current transmission station in real time; when a fault occurs in a high-voltage direct-current transmission system, if the AC commutation voltage is lower than a set voltage threshold, generating a direct-current current instruction value based on a direct-current current instruction prediction model obtained by system identification under the current fault; wherein the direct-current current instruction value considers a static security commutation boundary and increases an over-regulation amount, so as to achieve a control objective of preventing commutation failure. The application is based on the static security boundary and the direct-current current control characteristics of system identification, can accurately and dynamically adjust the current set value under a fault state, can effectively suppress the commutation failure phenomenon, and can quickly restore the normal operation state of the system after the fault.

Description

Technical Field

[0001] This invention relates to the field of power system control technology, and in particular to a commutation failure suppression method and apparatus based on static safety boundaries and predictive control, which is applied to high voltage direct current (HVDC) transmission systems for optimizing current control during fault transients. Background Technology

[0002] High-voltage direct current (HVDC) transmission systems play a crucial role in modern power transmission, especially in long-distance and high-capacity power transmission, where their economic efficiency and cost-effectiveness make them highly sought after. However, HVDC systems based on commutated converters (LCCs) may face the risk of commutation failure, which can lead to DC transmission interruptions, AC system instability, reactive power imbalance, and malfunctions or failures of protection devices, ultimately jeopardizing the overall system safety. Commutation failure is usually caused by AC system faults or voltage fluctuations, which can prevent the converter from functioning properly, thus affecting the stability and reliability of the entire power transmission system. While there are many existing optimization strategies for low-voltage DC current limiting control (VDCOL), their algorithms are complex, lack theoretical explanation, and rely mainly on simulation verification, making them difficult to apply in practical systems.

[0003] In traditional low-voltage current-limiting control, the VDCOL parameter is typically set to a fixed value, which limits the adjustment range of the firing angle. At low AC commutation voltages, this setting may be insufficient to prevent commutation failure, while at high voltages it limits the system's potential, resulting in underutilization of transmission capacity. Furthermore, when the system DC voltage fluctuates drastically, the VDCOL response may be untimely, potentially exacerbating commutation failure or causing drastic fluctuations in current command, leading to subsequent system failures. To address these challenges, recent research has proposed various optimization strategies, such as adaptive voltage limiting strategies and multi-electrical quantity control signal fusion, to improve the system's responsiveness to dynamic current changes. However, the complexity of these strategies and their dependence on standard test models make them difficult to implement in practical engineering applications. Summary of the Invention

[0004] The purpose of this invention is to overcome the shortcomings of existing technologies by proposing a commutation failure suppression method and apparatus based on static safety boundaries and predictive control, aiming to improve the stability and reliability of HVDC systems. Based on static safety boundaries and DC current control characteristics identified by the system, this invention precisely and dynamically adjusts the current setpoint under fault conditions, effectively suppressing commutation failure and quickly restoring the system to normal operation after a fault. This invention has good adaptability and operability, providing a reference for the optimization of future HVDC systems.

[0005] A first aspect of this invention proposes a commutation failure suppression method based on static safety boundaries and predictive control, comprising:

[0006] Real-time acquisition of AC commutation voltage in high-voltage direct current transmission stations;

[0007] When a fault occurs in the high-voltage direct current transmission system, if the AC commutation voltage is lower than the set voltage threshold, a DC current command value is generated based on the DC current command prediction model obtained by the system under the current fault. The DC current command value takes into account the static safety commutation boundary and adds over-adjustment to achieve the control objective of preventing commutation failure.

[0008] In one specific embodiment of the present invention, before generating the DC current command value based on the DC current command prediction model obtained by the system identification under the current fault, the method further includes:

[0009] Train the DC current command prediction model;

[0010] The training of the DC current command prediction model includes:

[0011] 1) By simulating the fault, the simulated DC current command value and AC commutation voltage, as well as the measured DC current value and the measured advance firing angle value are collected;

[0012] 2) Based on the data collected in step 1), the simulated DC current command value and AC commutation voltage at the moment of the fault occurrence are used as inputs. The measured DC current value and the measured advance firing angle value at that moment are used for fitting and comparison to form a training sample; all training samples constitute the training set.

[0013] 3) Based on the training set obtained in step 2), train the recognition model, and then obtain the transfer function from the recognition model;

[0014] 4) Perform Laplace transforms on the simulated DC current command step value and AC commutation voltage step value of the training sample, and substitute them into the transfer function to calculate the predicted DC current Laplace transform value and the predicted lead firing angle Laplace transform value corresponding to the training sample; perform inverse Laplace transforms on the two Laplace transform values ​​to obtain the predicted DC current value and the predicted lead firing angle value corresponding to each training sample.

[0015] Among them, the current command step value The Laplace transform function is:

[0016]

[0017] AC commutation voltage drop value The Laplace transform function is:

[0018]

[0019] Where a, b, and c are the drop coefficients for each segment; G1 and G2 are the transfer functions;

[0020] 5) Using the DC current prediction value and advance trigger angle prediction value corresponding to each training sample obtained in step 4), based on the static safety commutation boundary, the DC current command prediction value corresponding to each training sample is obtained.

[0021]

[0022]

[0023] Where n is the number of piecewise linear segments; U L为 AC commutation voltage, I ord The current command value is β; β is the lead firing angle, β = π - α, where α is the firing angle; I d The DC current at the static safety commutation boundary;

[0024] The static safety commutation boundary is represented as follows:

[0025]

[0026] In the formula, γ is the converter arc extinction angle; X c For commutation reactance, X c =ωL c .

[0027] In one specific embodiment of the present invention, it further includes:

[0028] When training the DC current command prediction model, the measured DC current values ​​are smoothed to remove noise, and then the transfer function is identified in the discrete time domain. Finally, the discrete transfer function is converted into a continuous model.

[0029] In one specific embodiment of the present invention, it further includes:

[0030] Once the control objective is achieved, the AC commutation voltage is restored and the DC current command value is increased to maintain normal commutation.

[0031] In one specific embodiment of the present invention, it further includes:

[0032] After the fault is cleared, the AC commutation voltage gradually increases to the normal level, and the system is kept running stably by adjusting the lead firing angle.

[0033] A second aspect of the present invention provides a commutation failure suppression device based on static safety boundaries and predictive control, comprising:

[0034] The voltage acquisition module is used to acquire the AC commutation voltage of the high-voltage direct current transmission station in real time.

[0035] The DC current command calculation module is used to generate a DC current command value based on the DC current command prediction model obtained by the system under the current fault when the AC commutation voltage is lower than the set voltage threshold during a fault in the high voltage DC transmission system. The DC current command value takes into account the static safety commutation boundary and adds an over-adjustment amount to achieve the control objective of preventing commutation failure.

[0036] In one specific embodiment of the present invention, before generating the DC current command value based on the DC current command prediction model obtained by the system identification under the current fault, the method further includes:

[0037] Train the DC current command prediction model;

[0038] The training of the DC current command prediction model includes:

[0039] 1) By simulating the fault, the simulated DC current command value and AC commutation voltage, as well as the measured DC current value and the measured advance firing angle value are collected;

[0040] 2) Based on the data collected in step 1), the simulated DC current command value and AC commutation voltage at the moment of the fault occurrence are used as inputs. The measured DC current value and the measured advance firing angle value at that moment are used for fitting and comparison to form a training sample; all training samples constitute the training set.

[0041] 3) Based on the training set obtained in step 2), train the recognition model, and then obtain the transfer function from the recognition model;

[0042] 4) Perform Laplace transforms on the simulated DC current command step value and AC commutation voltage step value of the training sample, and substitute them into the transfer function to calculate the predicted DC current Laplace transform value and the predicted lead firing angle Laplace transform value corresponding to the training sample; perform inverse Laplace transforms on the two Laplace transform values ​​to obtain the predicted DC current value and the predicted lead firing angle value corresponding to each training sample.

[0043] Among them, the current command step value The Laplace transform function is:

[0044]

[0045] AC commutation voltage drop value The Laplace transform function is:

[0046]

[0047] Where a, b, and c are the drop coefficients for each segment; G1 and G2 are the transfer functions;

[0048] 5) Using the DC current prediction value and advance trigger angle prediction value corresponding to each training sample obtained in step 4), based on the static safety commutation boundary, the DC current command prediction value corresponding to each training sample is obtained.

[0049]

[0050] Where n is the number of piecewise linear segments; U L为 AC commutation voltage, I ord The current command value is β; β is the lead firing angle, β = π - α, where α is the firing angle; I d The DC current at the static safety commutation boundary;

[0051] The static safety commutation boundary is represented as follows:

[0052]

[0053] In the formula, γ is the converter arc extinction angle; X c For commutation reactance, X c =ωL c .

[0054] In one specific embodiment of the present invention, it further includes:

[0055] When training the DC current command prediction model, the measured DC current values ​​are smoothed to remove noise, and then the transfer function is identified in the discrete time domain. Finally, the discrete transfer function is converted into a continuous model.

[0056] In one specific embodiment of the present invention, it further includes:

[0057] Once the control objective is achieved, the AC commutation voltage is restored and the DC current command value is increased to maintain normal commutation.

[0058] In one specific embodiment of the present invention, it further includes:

[0059] After the fault is cleared, the AC commutation voltage gradually increases to the normal level, and the system is kept running stably by adjusting the lead firing angle.

[0060] A third aspect of the present invention provides an electronic device comprising:

[0061] At least one processor; and a memory communicatively connected to said at least one processor;

[0062] The memory stores instructions that can be executed by the at least one processor, and the instructions are configured to perform the aforementioned commutation failure suppression method based on static safety boundaries and predictive control.

[0063] A fourth aspect of the present invention provides a computer-readable storage medium storing computer instructions for causing the computer to execute the above-described commutation failure suppression method based on static safety boundaries and predictive control.

[0064] The features and beneficial effects of this invention are as follows:

[0065] 1) Fast response speed: By monitoring the power grid status in real time, the current setpoint is quickly adjusted to ensure that the system can respond quickly when a fault occurs and avoid commutation failure.

[0066] 2) High stability: By introducing current rise rate limiting and dynamic adjustment mechanism, the system is ensured to remain stable during the recovery process after a fault, avoiding the occurrence of secondary faults.

[0067] 3) Easy to implement: No large-scale modification of the existing system is required. It is easy to integrate into the existing HVDC control system and has high engineering application value.

[0068] 4) High adaptability: It is suitable for a variety of fault scenarios and power grid conditions, and can provide effective control under different fault conditions to ensure the safe and reliable operation of the system. Attached Figure Description

[0069] Figure 1 This is an overall flowchart of a commutation failure suppression method based on static safety boundary and predictive control according to an embodiment of the present invention. Detailed Implementation

[0070] This invention proposes a commutation failure suppression method and apparatus based on static safety boundaries and predictive control, which will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0071] A first aspect of this invention proposes a commutation failure suppression method based on static safety boundaries and predictive control, comprising:

[0072] Real-time acquisition of AC commutation voltage in high-voltage direct current transmission stations;

[0073] When a fault occurs in the high-voltage direct current transmission system, if the AC commutation voltage is lower than the set voltage threshold, a DC current command value is generated based on the DC current command prediction model obtained by the system under the current fault. The DC current command value takes into account the static safety commutation boundary and adds over-adjustment to achieve the control objective of preventing commutation failure.

[0074] In a specific embodiment of the present invention, the overall process of the commutation failure suppression method based on static safety boundaries and predictive control is as follows: Figure 1 As shown, it includes the following steps:

[0075] 1) Real-time acquisition of AC commutation voltage U of high-voltage direct current transmission station L .

[0076] 2) When a fault occurs in the high-voltage direct current transmission system, the following determinations should be made:

[0077] If the AC commutation voltage U L The voltage drops below the set threshold U. f If the AC commutation voltage U..., proceed to step 2) to perform the operation to suppress commutation failure; if the AC commutation voltage U... L The drop did not fall below the threshold U f If so, there is no need to perform the subsequent commutation failure suppression step, and we return to step 1).

[0078] In this embodiment, in a relatively weak AC system (low short-circuit ratio), the voltage threshold U f To avoid false positives, the voltage threshold U may need to be increased appropriately (e.g., by 0.8 pu); however, in more powerful systems, a lower voltage threshold U can be selected. f (e.g., 0.7 pu). The specific threshold depends on the system design, such as the standard, the converter's firing angle margin, and the actual operating conditions.

[0079] 3) Based on AC commutation voltage U L By combining the preset DC current command prediction model under the current fault, the overshoot DC current command value is obtained to block the commutation failure.

[0080] In this embodiment, the DC current command prediction model essentially predicts the current command by back-calculating the station-valve control predictor and introduces overshoot to optimize the current recovery speed, controlling the DC current from two dimensions: amplitude and recovery time. This model utilizes nonlinear system piecewise identification and the least squares method to obtain the dual-input, dual-output transfer function of the DC current command value, AC commutation voltage on DC current, and lead firing angle.

[0081] Specifically, in this embodiment, the DC current command prediction model under any fault is established in the following way:

[0082] 3-1) By simulating the fault, the simulated DC current command value and AC commutation voltage, as well as the measured DC current value and the measured advance trigger angle value are collected.

[0083] In this embodiment, according to the basic requirements for relay protection in GB / T 38969-2020 Technical Guidelines for Power Systems, the fault clearing time for near-end and far-end faults on 220kV lines should not exceed 0.12s, for 330kV lines it should exceed 0.1s, and for 500kV and above lines it should not exceed 0.09s for near-end faults and 0.1s for far-end faults. Furthermore, in large power systems like the East China Power Grid, the fault information acquisition time for transmission lines is affected by various factors, including the response time of relay protection devices, fault recorders, and communication delays. Considering a communication transmission delay of 20ms, the fault information acquisition time τ for transmission lines is defined as follows. max =20ms, taking the output DC current command response time of the VDCOL module improved by the commutation failure suppression method based on static safety boundary and predictive control as t = 1.4τ. max =28ms. The sampling time is 0.0001s, and the data selected should cover the period during which the commutation failure occurred.

[0084] 3-2) Based on the data collected in step 3-1), the simulated DC current command value and AC commutation voltage at the moment of the fault occurrence are used as inputs. The measured DC current value and the measured advance firing angle value at that moment are used for fitting and comparison (actually, this is also a kind of input; the output is the DC current prediction value and the advance firing angle prediction value obtained by the identification model. The measured DC current value and the measured advance firing angle value are compared with the DC current prediction value and the advance firing angle prediction value obtained by identification to determine the accuracy of the DC current prediction value and the advance firing angle prediction value, and to debug the optimal transfer function) to form a training sample; all training samples constitute the training set.

[0085] 3-3) Based on the training set obtained in step 3-2), the identification model is trained using the MATLAB System Identification module, and then the transfer function is obtained from the identification model.

[0086] 3-4) Perform Laplace transforms on the simulated DC current command step value and AC commutation voltage step value of the training sample, and substitute them into the transfer function to calculate the predicted DC current Laplace transform value and the predicted lead firing angle Laplace transform value corresponding to the training sample. Perform inverse Laplace transforms on these two Laplace transform values ​​to obtain the predicted DC current value and the predicted lead firing angle value corresponding to each training sample.

[0087] Among them, the current command step value The Laplace transform function is:

[0088]

[0089] AC commutation voltage drop value The Laplace transform function is:

[0090]

[0091] Where a, b, and c are the drop coefficients for each segment; G1 and G2 are the transfer functions;

[0092] 3-5) Using the DC current prediction value and advance trigger angle prediction value corresponding to each training sample obtained in step 3-4), the DC current command prediction value corresponding to each training sample is obtained based on the static safety commutation boundary.

[0093]

[0094] Where n is the number of segments in the piecewise linear pattern.

[0095] This embodiment, based on the current command prediction value calculated according to the static safety commutation boundary, accelerates the DC current response by adding an overshoot to ensure that commutation failure does not occur.

[0096] In high-voltage direct current (HVDC) transmission systems, avoiding commutation failure is crucial for ensuring stable system operation. The static safe commutation boundary refers to the critical point or range at which the commutation device cannot function properly. Clarifying the boundary conditions for commutation failure provides a basis for researching and developing preventative measures, allowing for proactive measures to avoid commutation failures. The static safe commutation boundary is determined by the commutation circuit, the quasi-steady-state AC voltage, and the thyristor turn-off characteristics. L (AC commutation voltage), I d (DC current) and γ (extinguishing angle) are three key quantities characterizing its boundary constraints. L Determined by factors such as system voltage, I d The phase angle (extinction angle) of the AC system during arc extinction is indirectly controlled by the controller. These three factors work together to determine the position and stability of the commutation boundary and the maximum DC current (Io). d max When the voltage undergoes a sudden change or step change, after a control and primary circuit transient process, if the current actual DC current I... d Increase the DC current value I above the maximum active power that can be transmitted without commutation failure. d max Commutation failure will occur. Given a quasi-steady-state voltage and other relevant factors, a maximum current for DC operation, known as the static safe commutation boundary, can be determined. Furthermore, under low quasi-steady-state AC voltage conditions, once the DC current command value I... ord Commutation failure will occur if the static safety commutation boundary is exceeded.

[0097] The static safety commutation boundary during symmetrical operation can be expressed as:

[0098]

[0099] In the formula, γ is the converter arc extinction angle; I d The DC current at the static safety commutation boundary; X c For commutation reactance, X c =ωL c U L β is the AC commutation voltage; β is the leading trigger angle, β=π-α, where α is the trigger angle.

[0100] Due to the unsatisfactory results in continuous transfer function identification, this embodiment improves the accuracy of the model by smoothing and removing noise from the measured DC current values ​​when dealing with high-frequency oscillations. Furthermore, the system is modeled and analyzed in the discrete time domain, with a sampling interval of 0.0001s to ensure the capture of the system's dynamic characteristics. After identifying the discrete transfer function, the discrete model is converted into a continuous model using the d2c function provided by MATLAB. This facilitates further analysis and control design in the continuous time domain, thereby improving the overall effectiveness and accuracy of the system identification.

[0101] In this embodiment, after the model training is completed, under the current fault condition, the real-time AC commutation voltage U will be... L Input the model, and the model will output a DC current command value. Then, a new U is constructed based on the calculated command value. L -I ord Curve, U L As input, the output I guarantees maximum power transfer without commutation failure. ord That is, the current I ord max .

[0102] Furthermore, after commutation failure blocking, the method described in this embodiment also includes:

[0103] 4) Maintain normal commutation of the system by adjusting the DC current command value.

[0104] In this embodiment, improper DC system control, such as an excessively low current command, may lead to subsequent commutation failure. Therefore, the design and response of the control system are crucial to preventing such failures. During fault disturbances or dynamic voltage fluctuations, the control parameters are adjusted according to the system state, reducing the command value I. ord To quickly reduce the load and improve system safety. Once the control target is achieved, the AC commutation voltage U... L Rapid recovery, with the goal of quickly restoring DC transmission power and preventing further commutation failures, involves increasing the DC current and introducing a corrected IF.ord This suppresses commutation failure and limits the significant drop in output power. (This embodiment aims to mitigate the DC current I after fault clearance.) d To address the issues of slow recovery and excessive overshoot of the arc-extinguishing angle γ, and to ensure system stability while reducing electrical and thermal stress on equipment, the optimal balance must be found between rapid DC current recovery, avoiding overshoot and commutation failure, and protecting the equipment, ultimately restoring the arc-extinguishing angle γ to its intrinsic arc-extinguishing angle γ. min The current command value will be switched to the DC current I. d 80%. This measure aims to control the DC current command value I of the output VDCOL after a fault. ord The rapid increase in speed accelerates the system's DC current I d The recovery process limits the overshoot during arc extinction to maintain stable system operation and protect power equipment from damage caused by excessive current surges. This embodiment adaptively adjusts the ramp rate to suit the dynamic response characteristics of different systems, ensuring a smooth transition and avoiding unnecessary fluctuations.

[0105] 5) After the fault is cleared, the control system will attempt to restore normal operation. L It will gradually rise to a normal level, and the control system will adjust according to U. L and I d The change in U adjusts the lead-out angle β to maintain stable system operation. L Recover to a sufficiently high level, and I d When reduced to a controllable range, γ will increase, reducing the risk of commutation failure.

[0106] If no subsequent commutation failure occurs, the system returns to normal, and then returns to step 1).

[0107] The method described in this embodiment will be further explained in detail below with reference to a specific example.

[0108] In this embodiment, several sets of step current signal commands ΔI are set in the East China Power Grid. ord Signal, AC commutation voltage drop ΔU L The signal simulates the situation where, after a segmented simulation fault occurs, the improved VDCOL module based on static safety boundaries and predictive control commutation failure suppression method takes effect, thus suppressing the commutation failure. The system response values ​​(lead firing angle, DC current) are obtained:

[0109] Table 1. Linear parameters of the VDCOL module improved by the commutation failure suppression method based on static safety boundary and predictive control in a specific embodiment of the present invention.

[0110]

[0111] According to the basic requirements for relay protection in GB / T 38969-2020 Technical Guidelines for Power Systems, the clearing time for near-end and far-end faults on 220kV lines should not exceed 0.12s; for 330kV lines, the clearing time should exceed 0.1s; and for 500kV and above lines, the clearing time for near-end faults should not exceed 0.09s, and the clearing time for far-end faults should not exceed 0.1s. Furthermore, in large power systems like the East China Power Grid, the information acquisition time for transmission line faults is affected by various factors, including the response time of relay protection devices, fault recorders, and communication delays. Considering a communication transmission delay of 20ms, let τ be defined. max =20ms, take the response time t=1.4τ max =28ms.

[0112] Select the identification data, and use the MATLAB System Identification module to identify the transfer function of this two-input two-output system, thereby obtaining its mathematical model:

[0113] Table 2. Identification results of piecewise continuous transfer functions in a specific embodiment of the present invention.

[0114]

[0115]

[0116] To improve the poor performance in continuous transfer function identification, this embodiment improves the accuracy of the model by smoothing and removing noise from the system's DC current response value when dealing with high-frequency oscillations.

[0117] Meanwhile, the system was modeled and analyzed in the discrete time domain, with a sampling interval of 0.0001s chosen to ensure the capture of the system's dynamic characteristics. After identifying the discrete transfer function, the discrete model was converted into a continuous model using the d2c function provided by MATLAB. This facilitates further analysis and control design in the continuous time domain, thereby improving the overall effectiveness and accuracy of the system identification.

[0118] Table 3. Identification results of piecewise discrete transfer function in a specific embodiment of the present invention.

[0119]

[0120]

[0121] Current command step value The Laplace transform function is:

[0122]

[0123] AC commutation voltage drop value The Laplace transform function is:

[0124]

[0125] The Laplace transforms of the output response current and lead firing angle are obtained from the two Laplace transform functions and each transfer function mentioned above. Then, the inverse Laplace transform is performed to calculate the predicted DC current and lead firing angle for each segment:

[0126]

[0127] In order to shorten the response time of the power system and make the DC current I d To achieve the target value A more quickly, this embodiment will control instruction I. ord The target DC current value A is set to be greater than the target value A. This is done to utilize the dynamic response characteristics of the system, accelerating the system state change process by providing a larger initial control input. However, when implementing the method described in this embodiment, it must be ensured that the target DC current value A is positive, and that system parameters and safety limits are fully considered to prevent overshoot or other unstable behaviors.

[0128] In the East China Power Grid, the inherent arc extinction angle γ0 = 7°, and the minimum arc extinction angle γ min =17°. In currently widely used electromechanical transient simulation programs for AC / DC power systems, DC converters generally adopt quasi-steady-state models. During calculations, the leakage reactance of the converter transformer is taken as the commutation reactance. Therefore, X c The leakage withstand value is 0.189 * 2 = 0.378 pu.

[0129] Table 4. Parameters of the East China Power Grid used in a specific embodiment of the present invention.

[0130] parameter <![CDATA[γ0]]> 7° <![CDATA[γ min ]]> 17° <![CDATA[X c ]]> 0.189pu

[0131] Substituting the static safety commutation boundary, the calculated response time of the VDCOL module output DC current command based on the improved commutation failure suppression method using static safety boundary and predictive control is t = 1.4τ. max =28ms is the range of DC current command values ​​that ensures the system can block commutation failure and operate safely and stably.

[0132] To achieve the above embodiments, a second aspect of the present invention provides a commutation failure suppression device based on static safety boundaries and predictive control, comprising:

[0133] The voltage acquisition module is used to acquire the AC commutation voltage of the high-voltage direct current transmission station in real time.

[0134] The DC current command calculation module is used to generate a DC current command value based on the DC current command prediction model obtained by the system under the current fault when the AC commutation voltage is lower than the set voltage threshold during a fault in the high voltage DC transmission system. The DC current command value takes into account the static safety commutation boundary and adds an over-adjustment amount to achieve the control objective of preventing commutation failure.

[0135] In one specific embodiment of the present invention, before generating the DC current command value based on the DC current command prediction model obtained by the system identification under the current fault, the method further includes:

[0136] Train the DC current command prediction model;

[0137] The training of the DC current command prediction model includes:

[0138] 1) By simulating the fault, the simulated DC current command value and AC commutation voltage, as well as the measured DC current value and the measured advance firing angle value are collected;

[0139] 2) Based on the data collected in step 1), the simulated DC current command value and AC commutation voltage at the moment of the fault occurrence are used as inputs. The measured DC current value and the measured advance firing angle value at that moment are used for fitting and comparison to form a training sample; all training samples constitute the training set.

[0140] 3) Based on the training set obtained in step 2), train the recognition model, and then obtain the transfer function from the recognition model;

[0141] 4) Perform Laplace transforms on the simulated DC current command step value and AC commutation voltage step value of the training sample, and substitute them into the transfer function to calculate the predicted DC current Laplace transform value and the predicted lead firing angle Laplace transform value corresponding to the training sample; perform inverse Laplace transforms on the two Laplace transform values ​​to obtain the predicted DC current value and the predicted lead firing angle value corresponding to each training sample.

[0142] Among them, the current command step value The Laplace transform function is:

[0143]

[0144] AC commutation voltage drop value The Laplace transform function is:

[0145]

[0146] Where a, b, and c are the drop coefficients for each segment; G1 and G2 are the transfer functions;

[0147] 5) Using the DC current prediction value and advance trigger angle prediction value corresponding to each training sample obtained in step 4), based on the static safety commutation boundary, the DC current command prediction value corresponding to each training sample is obtained.

[0148]

[0149] Where n is the number of piecewise linear segments; U L为 AC commutation voltage, I ord The current command value is β; β is the lead firing angle, β = π - α, where α is the firing angle; I d The DC current at the static safety commutation boundary;

[0150] The static safety commutation boundary is represented as follows:

[0151]

[0152] In the formula, γ is the converter arc extinction angle; X c For commutation reactance, X c =ωL c .

[0153] In one specific embodiment of the present invention, it further includes:

[0154] When training the DC current command prediction model, the measured DC current values ​​are smoothed to remove noise, and then the transfer function is identified in the discrete time domain. Finally, the discrete transfer function is converted into a continuous model.

[0155] In one specific embodiment of the present invention, it further includes:

[0156] Once the control objective is achieved, the AC commutation voltage is restored and the DC current command value is increased to maintain normal commutation.

[0157] In one specific embodiment of the present invention, it further includes:

[0158] After the fault is cleared, the AC commutation voltage gradually increases to the normal level, and the system is kept running stably by adjusting the lead firing angle.

[0159] This enables DC current control characteristics based on static safety boundaries and system identification, allowing for precise dynamic adjustment of the current setpoint under fault conditions, and introducing a DC current rise rate limiting mechanism. In this way, commutation failure can be effectively suppressed, and the system can be quickly restored to normal operation after a fault.

[0160] To implement the above embodiments, a third aspect of the present invention provides an electronic device, comprising:

[0161] At least one processor; and a memory communicatively connected to said at least one processor;

[0162] The memory stores instructions that can be executed by the at least one processor, and the instructions are configured to perform the aforementioned commutation failure suppression method based on static safety boundaries and predictive control.

[0163] To implement the above embodiments, a fourth aspect of the present invention provides a computer-readable storage medium storing computer instructions for causing the computer to execute the above-described commutation failure suppression method based on static safety boundaries and predictive control.

[0164] It should be noted that the computer-readable medium described in this disclosure can be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium can be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this disclosure, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in connection with an instruction execution system, apparatus, or device. In this disclosure, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium can be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wires, optical fibers, RF (radio frequency), etc., or any suitable combination thereof.

[0165] The aforementioned computer-readable medium may be included in the aforementioned electronic device; or it may exist independently and not assembled into the electronic device. The aforementioned computer-readable medium carries one or more programs, which, when executed by the electronic device, cause the electronic device to perform a commutation failure suppression method based on static safety boundaries and predictive control according to the above embodiments.

[0166] Computer program code for performing the operations of this disclosure can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0167] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0168] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "multiple" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0169] Any process or method described in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or more executable instructions for implementing a particular logical function or process, and the scope of the preferred embodiments of this application includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the function involved, as will be understood by those skilled in the art to which embodiments of this application pertain.

[0170] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include: an electrical connection having one or more wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Furthermore, computer-readable media can even be paper or other suitable media on which programs can be printed, because programs can be obtained electronically, for example, by optically scanning the paper or other media, followed by editing, interpreting, or otherwise processing as necessary, and then stored in computer memory.

[0171] It should be understood that various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0172] Those skilled in the art will understand that all or part of the steps of the methods described in the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, it includes one or a combination of the steps of the method embodiments.

[0173] Furthermore, the functional units in the various embodiments of this application can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0174] The storage medium mentioned above can be a read-only memory, a disk, or an optical disk, etc. Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of this application.

Claims

1. A static security boundary and predictive control based commutation failure mitigation method, characterized in that, The method comprises the steps of: real-time acquisition of AC commutation voltage of a high-voltage direct-current power station; when a fault occurs in the high-voltage direct-current power system, if the AC commutation voltage is lower than a set voltage threshold, a direct-current current instruction value is generated based on a direct-current current instruction prediction model obtained by system identification under the current fault; wherein the direct-current current instruction value considers a static safety commutation boundary and increases an over-regulation amount to achieve a control objective of preventing commutation failure; wherein before the direct-current current instruction value is generated based on the direct-current current instruction prediction model obtained by system identification under the current fault, the method further comprises the steps of: training the direct-current current instruction prediction model; the step of training the direct-current current instruction prediction model comprises the steps of: 1) collecting simulated direct-current current instruction values and AC commutation voltages, and direct-current current measured values and lead trigger angle measured values by simulating the fault; 2) based on the data collected in step 1), the simulated direct-current current instruction value and the AC commutation voltage at the time of fault occurrence are taken as inputs, and the direct-current current measured value and the lead trigger angle measured value at this time are used for fitting comparison to form a training sample; all training samples constitute a training set; 3) based on the training set obtained in step 2), an identification model is trained, and then a transfer function is obtained from the identification model; 4) Laplace transforms are respectively performed on the simulated direct-current current instruction step value and the AC commutation voltage step value of the training sample, and the transfer function is substituted to calculate the direct-current current prediction Laplace transform value and the lead trigger angle prediction Laplace transform value corresponding to the training sample; inverse Laplace transforms are respectively performed on the two Laplace transform values to obtain the direct-current current prediction value and the lead trigger angle prediction value corresponding to each training sample; Wherein, the current instruction step value The Laplace transform function of the above equation is: AC commutation voltage dip value The Laplace transform function of the above equation is: 5) based on the static safety commutation boundary, the direct-current current instruction prediction value corresponding to each training sample is obtained by using the direct-current current prediction value and the lead trigger angle prediction value corresponding to each training sample obtained in step 4); wherein n is the number of piecewise linear segments; U L is the AC commutation voltage, I ord is the DC current command value; β is the advance firing angle, β = π - a, wherein a is the firing angle; I d is the DC current of the static security commutation boundary; a, b, c are the drop value coefficients of each segment; G1, G2 are the transfer functions; wherein the static safety commutation boundary is expressed as: where γ is the commutator quenching angle; X c is the commutation reactance, X c = ωL c .

2. The method of claim 1, wherein, the method further comprises the steps of: when training the direct-current current instruction prediction model, the direct-current current measured value is subjected to smoothing and noise removal processing, and then the transfer function is identified in the discrete time domain, and the discrete transfer function is converted into a continuous model.

3. The method of claim 1, wherein, the method further comprises the steps of: after the control objective is achieved, the AC commutation voltage is restored, and the direct-current current instruction value is increased to maintain normal commutation.

4. The method of claim 3, wherein, the method further comprises the steps of: after the fault is cleared, the AC commutation voltage gradually increases to a normal level, and the lead trigger angle is adjusted to maintain stable operation of the system.

5. A static security boundary and predictive control based commutation failure mitigation device, characterized in that, The method comprises the steps of: a voltage acquisition module for real-time acquisition of AC commutation voltage of a high-voltage direct-current power station; a direct-current current instruction calculation module for generating a direct-current current instruction value based on a direct-current current instruction prediction model obtained by system identification under the current fault when a fault occurs in the high-voltage direct-current power system, if the AC commutation voltage is lower than a set voltage threshold; wherein the direct-current current instruction value considers a static safety commutation boundary and increases an over-regulation amount to achieve a control objective of preventing commutation failure; Wherein, before generating the DC current command value by the DC current command prediction model obtained by system identification under the current fault, it further comprises: training the DC current command prediction model; The training of the DC current command prediction model comprises: 1) Collecting simulated DC current command values and AC commutation voltages, and DC current measured values and lead trigger angle measured values by simulating the fault; 2) Based on the data collected in step 1), the simulated DC current command value and the AC commutation voltage at the fault occurrence time are taken as input, and the DC current measured value and the lead trigger angle measured value at this time are used for fitting comparison to form a training sample; all training samples constitute a training set; 3) Based on the training set obtained in step 2), the identification model is trained, and then the transfer function is obtained by the identification model; 4) Laplace transform is performed on the simulated DC current command step value and the AC commutation voltage step value of the training sample respectively, and is substituted into the transfer function for calculation to obtain the DC current prediction Laplace transform value and the lead trigger angle prediction Laplace transform value corresponding to the training sample; the two Laplace transform values are respectively subjected to inverse Laplace transform to obtain the DC current prediction value and the lead trigger angle prediction value corresponding to each training sample; Wherein, the current instruction step value The Laplace transform function of the current instruction step value is: AC commutation voltage dip value The Laplace transform function of the above equation is: Wherein, a, b, c are the drop value coefficients of each section; G1, G2 are the transfer function; 5) Based on the static security commutation boundary, the DC current command prediction value corresponding to each training sample is obtained by using the DC current prediction value and the lead trigger angle prediction value corresponding to each training sample obtained in step 4); wherein n is the number of piecewise linear segments; U L is the AC commutation voltage, I ord is the DC current command value; β is the advance firing angle, β = π - α, wherein α is the firing angle; I d is the DC current at the static security commutation boundary; Wherein, the static security commutation boundary is expressed as: where γ is the commutator quenching angle; X c is the commutation reactance, X c = ωL c .

6. The apparatus of claim 5, wherein, It further comprises: When training the DC current command prediction model, the DC current measured value is subjected to smoothing and noise removal processing, and then the transfer function is identified in the discrete time domain, and the discrete transfer function is converted into a continuous model.

7. The apparatus of claim 5, wherein, It further comprises: After the control target is achieved, the AC commutation voltage is restored, and the DC current command value is improved to maintain normal commutation.

8. The apparatus of claim 6, wherein, It further comprises: After the fault is cleared, the AC commutation voltage gradually rises to the normal level, and the lead trigger angle is adjusted to maintain the stable operation of the system.

Images