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

Abstract

The invention 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 alternating-current commutation voltage of a high-voltage direct-current power transmission station in real time; when the high-voltage direct-current power transmission system breaks down, if the alternating-current commutation voltage is lower than a set voltage threshold value, a direct-current instruction value is generated based on a direct-current instruction prediction model obtained through system identification under the current fault; wherein the direct current instruction value considers a static safety commutation boundary, and an overregulation amount is increased, so that a control target of preventing commutation failure is realized. Based on the static safety boundary and the direct current control characteristics of system identification, the current set value is accurately and dynamically adjusted in the fault state, the commutation failure phenomenon can be effectively inhibited, and the normal operation state of the system is rapidly recovered after the fault.

Description

Technical Field

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

[0002] High-voltage direct current (HVDC) transmission systems play a vital role in modern power transmission, especially in long-distance and large-capacity power transmission, where their economy and efficiency make them highly favored. However, HVDC systems based on phase-commutating converters (LCCs) may face the risk of commutation failure, which can lead to DC power outages, AC system instability, reactive power imbalance, and malfunction or refusal of protection equipment, thereby endangering the overall safety of the system. Commutation failure is usually caused by AC system faults or voltage fluctuations, which can cause the converter to fail to work properly, thereby affecting the stability and reliability of the entire power transmission system. Although there are many types of existing DC low-voltage current limiting control (VDCOL) optimization strategies, their algorithms are complex, lack theoretical explanations, and mainly rely on simulation verification, making them difficult to apply in actual systems.

[0003] In traditional low-voltage current limiting control, the VDCOL parameter is usually set to a fixed value, which limits the adjustment range of the trigger angle. At low AC commutation voltages, this setting may not be sufficient to prevent commutation failures, while at high voltages it limits the potential of the system, resulting in underutilization of the power transmission capacity. In addition, when the system DC voltage fluctuates violently, the VDCOL response may not be timely, potentially exacerbating commutation failures or causing violent fluctuations in current commands, leading to subsequent system failures. To address these challenges, recent studies have proposed a variety of optimization strategies, such as adaptive voltage limit strategies and multi-electrical quantity control signal fusion, to improve the system's ability to respond to dynamic changes in current. However, the complexity of these strategies and their reliance on standard test models make them difficult to apply in actual engineering applications. Summary of the invention

[0004] The purpose of the present invention is to overcome the shortcomings of the prior art and propose a method and device for suppressing commutation failure based on static safety margin and predictive control, aiming to improve the stability and reliability of the HVDC system. The present invention is based on the DC current control characteristics of static safety margin and system identification, accurately and dynamically adjusts the current setting value under the fault state, can effectively suppress the commutation failure phenomenon, and quickly restore the normal operation state of the system after the fault. The present invention has good adaptability and operability, and provides a reference for the optimization of future HVDC systems.

[0005] The first embodiment of the present invention provides a commutation failure suppression method based on static safety margin and predictive control, comprising:

[0006] Obtain the AC commutation voltage of the HVDC transmission station in real time;

[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 a DC current command prediction model obtained through system identification under the current fault; wherein the DC current command value takes into account the static safe commutation boundary and increases the overshoot to achieve the control goal of preventing commutation failure.

[0008] In a specific embodiment of the present invention, before the DC current command prediction model obtained by system identification under the current fault is used to generate the DC current command value, the method further includes:

[0009] Training the DC current command prediction model;

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

[0011] 1) By simulating the fault, collecting the simulated DC current command value and AC commutation voltage, as well as the DC current measured value and the leading trigger angle measured value;

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

[0013] 3) Based on the training set obtained in step 2), the identification model is trained, and then the transfer function is obtained from the identification model;

[0014] 4) Performing Laplace transform on the simulated DC current command step value and AC commutation voltage step value of the training sample respectively, and substituting them into the transfer function for calculation, to obtain the DC current predicted Laplace transform value and the advanced trigger angle predicted Laplace transform value corresponding to the training sample; performing inverse Laplace transform on the two Laplace transform values ​​respectively, to obtain the DC current predicted value and the advanced trigger angle predicted value corresponding to each training sample;

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

[0016]

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

[0018]

[0019] Among them, a, b, c are the drop value coefficients of each section; G1 and G2 are transfer functions;

[0020] 5) using the DC current prediction value and the leading trigger angle prediction value corresponding to each training sample obtained in step 4), based on the static safe commutation boundary, to obtain the DC current command prediction value corresponding to each training sample;

[0021]

[0022]

[0023] Where n is the number of segmented line segments; U L为 AC commutation voltage, I ord is the DC current command value; β is the leading trigger angle, β = π-α, where α is the trigger angle; I d is the DC current of the static safety commutation boundary;

[0024] Among them, the static safe commutation boundary is expressed as:

[0025]

[0026] Where, γ is the inverter extinction angle; X c is the commutation reactance, X c =ωL c .

[0027] In a specific embodiment of the present invention, it also includes:

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

[0029] In a specific embodiment of the present invention, it also includes:

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

[0031] In a specific embodiment of the present invention, it also includes:

[0032] After the fault is cleared, the AC commutation voltage gradually increases to a normal level, and the leading trigger angle is adjusted to maintain stable operation of the system.

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

[0034] A voltage acquisition module is used to obtain the AC commutation voltage of the high-voltage DC transmission station in real time;

[0035] A DC current command calculation module is used to generate a DC current command value based on a DC current command prediction model obtained through system identification under the current fault when a fault occurs in the high-voltage DC transmission system and if the AC commutation voltage is lower than a set voltage threshold; wherein the DC current command value takes into account the static safe commutation boundary and increases the overshoot to achieve the control goal of preventing commutation failure.

[0036] In a specific embodiment of the present invention, before the DC current command prediction model obtained by system identification under the current fault is used to generate the DC current command value, the method further includes:

[0037] Training the DC current command prediction model;

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

[0039] 1) By simulating the fault, collecting the simulated DC current command value and AC commutation voltage, as well as the DC current measured value and the leading trigger angle measured value;

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

[0041] 3) Based on the training set obtained in step 2), the identification model is trained, and then the transfer function is obtained from the identification model;

[0042] 4) Performing Laplace transform on the simulated DC current command step value and AC commutation voltage step value of the training sample respectively, and substituting them into the transfer function for calculation, to obtain the DC current predicted Laplace transform value and the advanced trigger angle predicted Laplace transform value corresponding to the training sample; performing inverse Laplace transform on the two Laplace transform values ​​respectively, to obtain the DC current predicted value and the advanced trigger angle predicted value corresponding to each training sample;

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

[0044]

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

[0046]

[0047] Among them, a, b, c are the drop value coefficients of each section; G1 and G2 are transfer functions;

[0048] 5) using the DC current prediction value and the leading trigger angle prediction value corresponding to each training sample obtained in step 4), based on the static safe commutation boundary, to obtain the DC current command prediction value corresponding to each training sample;

[0049]

[0050] Where n is the number of segmented line segments; U L为 AC commutation voltage, I ord is the DC current command value; β is the leading trigger angle, β = π-α, where α is the trigger angle; I d is the DC current of the static safety commutation boundary;

[0051] Among them, the static safe commutation boundary is expressed as:

[0052]

[0053] Where, γ is the inverter extinction angle; X c is the commutation reactance, X c =ωL c .

[0054] In a specific embodiment of the present invention, it also includes:

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

[0056] In a specific embodiment of the present invention, it also includes:

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

[0058] In a specific embodiment of the present invention, it also includes:

[0059] After the fault is cleared, the AC commutation voltage gradually increases to a normal level, and the leading trigger angle is adjusted to maintain stable operation of the system.

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

[0061] at least one processor; and a memory communicatively coupled to the at least one processor;

[0062] The memory stores instructions executable by the at least one processor, and the instructions are configured to execute the above-mentioned commutation failure suppression method based on static safety margin and predictive control.

[0063] A fourth aspect of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable the computer to execute the above-mentioned method for suppressing commutation failure based on static safety margin and predictive control.

[0064] The characteristics and beneficial effects of the present invention are:

[0065] 1) Fast response speed: By real-time monitoring of the grid status, the current setting value can be 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 limitation 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 implementation: No large-scale transformation of the existing system is required, and it is easy to integrate into the existing HVDC control system, with high engineering application value.

[0068] 4) Strong adaptability: It is applicable to a variety of fault scenarios and grid conditions, and can provide effective control under different fault conditions to ensure the safe and reliable operation of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0069] Figure 1 It is an overall flow chart of a commutation failure suppression method based on static safety margin and predictive control according to an embodiment of the present invention. DETAILED DESCRIPTION

[0070] The present invention proposes a commutation failure suppression method and device based on static safety margin and predictive control, which is further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0071] The first embodiment of the present invention provides a commutation failure suppression method based on static safety margin and predictive control, comprising:

[0072] Obtain the AC commutation voltage of the HVDC transmission station in real time;

[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 a DC current command prediction model obtained through system identification under the current fault; wherein the DC current command value takes into account the static safe commutation boundary and increases the overshoot to achieve the control goal of preventing commutation failure.

[0074] In a specific embodiment of the present invention, the commutation failure suppression method based on static safety margin and predictive control has the following overall process: Figure 1 As shown, the following steps are included:

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

[0076] 2) When a fault occurs in the high-voltage DC transmission system, determine:

[0077] If the AC commutation voltage U L Drops below the set voltage threshold U f , then go to step 2) to suppress commutation failure; if the AC commutation voltage U L The drop does not fall below the threshold U f , then there is no need to perform the subsequent commutation failure suppression step, and return to step 1).

[0078] In this embodiment, in a weaker AC system (short circuit is relatively low), the voltage threshold U f It may be necessary to increase it appropriately (e.g. 0.8pu) to avoid misjudgment; in a stronger system, a lower voltage threshold U f (e.g. 0.7pu). The specific threshold depends on the system design, such as the standard, the inverter firing angle margin and the actual operating conditions.

[0079] 3) Based on AC commutation voltage U L , combined with the preset DC current command prediction model under the current fault, the over-adjusted DC current command value is obtained to block the commutation failure.

[0080] In this embodiment, the DC current command prediction model is essentially to reversely predict the current command through the station-valve control predictor, and introduce overshoot to optimize the current recovery speed, and control the DC current from two dimensions: amplitude and recovery time). The model uses nonlinear system segmented identification and least squares method (Least Squares) to obtain the dual-input and dual-output transfer function of the DC current command value, the AC commutation voltage to the DC current, and the leading trigger angle.

[0081] Specifically, the DC current instruction prediction model under any fault in this embodiment 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 actual measured value of the DC current and the actual measured value of the leading trigger angle 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 near-end and far-end fault removal time for 220kV lines is no more than 0.12s, the near-end and far-end fault removal time for 330kV lines is greater than 0.1s, and the near-end fault removal time for 500kV and above lines is no more than 0.09s, and the far-end fault removal time is no more than 0.1s. In large power systems such as the East China Power Grid, the transmission line fault information collection time is affected by many factors, including the response time of the relay protection device, the fault recorder, and the communication delay, etc. Considering that the communication transmission delay is 20ms. Define the transmission line fault information collection time τ max =20ms, the output DC current command response time of the VDCOL module improved by the commutation failure suppression method based on static safety margin and predictive control is t=1.4τ max =28ms. The sampling time is 0.0001s, and the data selection covers the data during the period when the commutation failure occurs.

[0084] 3-2) Based on the data collected in step 3-1), the simulated DC current command value and AC commutation voltage at the time of fault occurrence are used as input, and the actual measured DC current value and the actual measured value of the lead trigger angle at that moment are used for fitting and comparison (actually, it is also a kind of input, and the output is the DC current prediction value and the lead trigger angle prediction value obtained by the identification model. The actual measured DC current value and the actual measured value of the lead trigger angle are compared with the DC current prediction value and the lead trigger angle prediction value obtained by identification to determine the accuracy of the DC current prediction value and the lead trigger angle prediction value, and debug the best transfer function) to form a training sample; all training samples constitute a 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 transform 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 for calculation to obtain the DC current prediction Laplace transform value and the advanced trigger angle prediction Laplace transform value corresponding to the training sample. Perform inverse Laplace transform on the two Laplace transform values ​​to obtain the DC current prediction value and the advanced trigger angle prediction value corresponding to each training sample.

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

[0088]

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

[0090]

[0091] Among them, a, b, c are the drop value coefficients of each section; G1 and G2 are transfer functions;

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

[0093]

[0094] Where n is the number of segmented line segments.

[0095] In this embodiment, based on the current command prediction value obtained by calculating according to the static safe commutation boundary, an overshoot is added to accelerate the DC current response to ensure that commutation failure does not occur.

[0096] In high-voltage direct current transmission systems, avoiding commutation failure is the key to ensuring stable operation of the system. The static safe commutation boundary refers to the critical point or range where the commutation device cannot work normally. Clarifying the boundary conditions of commutation failure will help provide a basis for the research and formulation of preventive measures for commutation failure accidents, and take corresponding measures in advance to avoid commutation failure. The static safe commutation boundary is determined by the commutation circuit, quasi-steady-state AC voltage and thyristor turn-off characteristics. L (AC commutation voltage), I d (DC current), γ (arc extinction angle) are the three key quantities that characterize its boundary constraints, U L Determined by factors such as system voltage, I d The phase angle (arc extinction angle) of the AC system when the arc is extinguished is indirectly controlled by the controller. The three together determine the position and stability of the commutation boundary and the maximum DC current (I d max ). When the voltage changes suddenly or in steps, after the control and primary circuit transition process, if the 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 the quasi-steady-state voltage and other related factors, a maximum current for DC operation can be determined, namely the static safe commutation boundary. In addition, under the condition of low quasi-steady-state AC voltage, once the DC current command value I ord If the static safe commutation boundary is exceeded, commutation failure will occur.

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

[0098]

[0099] Where, γ is the inverter extinction angle; I d is the DC current of the static safety commutation boundary; X c is the commutation reactance, X c =ωL c ; U L is the AC commutation voltage; β is the leading trigger angle, β=π-α, where α is the trigger angle.

[0100] Due to the problem of poor effect in the continuous transfer function identification process, when dealing with high-frequency oscillations, this embodiment improves the accuracy of the model by smoothing the measured value of the DC current to remove noise, and instead models and analyzes the system in the discrete time domain, and selects a sampling time interval of 0.0001s to ensure that the dynamic characteristics of the system can be captured. After completing the identification of the discrete transfer function, the d2c function provided by MATLAB is used to convert the discrete model into a continuous model, which is helpful for further analysis and control design in the continuous time domain, thereby improving the overall effect and accuracy of system identification.

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

[0102] Furthermore, after the commutation failure is blocked, the method described in this embodiment further includes:

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

[0104] In this embodiment, if the DC system control is improperly handled, such as the current command is too low, subsequent commutation failure may occur. Therefore, the design and response of the control system are crucial to prevent subsequent commutation failure. In the event of fault interference or dynamic voltage fluctuation, the control parameters are adjusted according to the system state to reduce the command value I ord To quickly reduce the load and improve the safety of the system. When the control target is reached, the AC commutation voltage U L Rapid recovery, with the goal of quickly restoring DC power transmission and preventing commutation failure again, increases DC current and introduces a corrected Iord , thereby suppressing commutation failure and limiting the sharp drop in output power. (This embodiment is to alleviate the DC current I after the fault is cleared d The problem of slow recovery and excessive overshoot of the arc extinction angle γ is solved to ensure system stability, reduce the electrical and thermal stress of the equipment, find the best balance between quickly restoring the DC current, avoiding overshoot and commutation failure, and protecting the equipment, and restore the arc extinction angle γ to the inherent arc extinction angle γ. min When the current command value is switched to the DC current I d This measure aims to control the output DC current command value I through VDCOL after the fault. ord Rapid increase in system DC current I d The overshoot during the arc extinction process is limited to maintain the stable operation of the system and protect the power equipment from damage caused by excessive current shock.) This embodiment adaptively adjusts the climbing rate according to the dynamic response characteristics of different systems to ensure a smooth transition and avoid unnecessary fluctuations.

[0105] 5) After the fault is cleared, the control system will try to restore normal operation. L will gradually increase to normal levels, and the control system will L and I d The change of U adjusts the leading trigger angle β to maintain the stable operation of the system. L Restored to a sufficiently high level, and I d When it is 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 is further described in detail below in conjunction with a specific embodiment.

[0108] In this embodiment, by setting several groups of step current signal instructions ΔI in the East China power grid, ord Signal, AC commutation voltage drop ΔU L The signal is simulated in sections. After the fault occurs, the improved VDCOL module based on the static safety boundary and predictive control commutation failure suppression method works to suppress the commutation failure, and the system response value (advanced trigger angle, DC current) is obtained:

[0109] Table 1: Linear parameters of VDCOL module improved by commutation failure suppression method based on static safety margin and predictive control in a specific implementation 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 clearance time for near-end and far-end faults of 220kV lines shall not exceed 0.12s, the clearance time for near-end and far-end faults of 330kV lines shall be greater than 0.1s, and the clearance time for near-end faults of 500kV and above lines shall not exceed 0.09s, and the clearance time for far-end faults shall not exceed 0.1s. In large power systems such as the East China Power Grid, the collection time of transmission line fault information is affected by many factors, including the response time of relay protection devices, fault recorders, and communication delays. The communication transmission delay is considered to be 20ms. Define τ max =20ms, take the response time t=1.4τ max =28ms.

[0112] Select the identification data, and use the obtained results to identify the transfer function of the dual-input dual-output system through the MATLAB System Identification module, and obtain its mathematical model respectively:

[0113] Table 2: Table of identification results of piecewise continuous transfer function in a specific embodiment of the present invention

[0114]

[0115]

[0116] In order to improve the problem of poor effect in the continuous transfer function identification process, when processing high-frequency oscillations, this embodiment improves the accuracy of the model by smoothing the system DC current response value to remove noise.

[0117] At the same time, the system is modeled and analyzed in the discrete time domain, and the sampling time interval is selected as 0.0001s to ensure that the dynamic characteristics of the system can be captured. After completing the identification of the discrete transfer function, the d2c function provided by MATLAB is used to convert the discrete model into a continuous model, which is helpful for further analysis and control design in the continuous time domain, thereby improving the overall effect and accuracy of system identification.

[0118] Table 3: Segmented discrete transfer function identification results in a specific embodiment of the present invention

[0119]

[0120]

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

[0122]

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

[0124]

[0125] The Laplace transform of the output response current and the leading trigger angle is obtained by the above two Laplace transform functions and each transfer function, and an inverse Laplace transform is performed on them to calculate the predicted value of each section of DC current and the predicted value of the leading trigger angle:

[0126]

[0127] In order to shorten the response time of the power system and make the DC current I d The output reaches the target value A faster. In this embodiment, the control instruction I ord The target DC current value A is set to a value greater than the target value A. This is done to utilize the dynamic response characteristics of the system and to accelerate the change process of the system state by providing a larger initial control input. However, when implementing the method described in this embodiment, it is necessary to ensure that the target DC current value A itself 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 the widely used electromechanical transient simulation programs for AC and DC power systems, the DC converter generally adopts a quasi-steady-state model. The leakage reactance of the converter transformer is taken as the commutation reactance during calculation. Therefore, X c The leakage reactance value is taken as 0.189*2=0.378pu.

[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 output DC current command response time of the VDCOL module improved by the commutation failure suppression method based on the static safety boundary and predictive control is t=1.4τ. max =28ms to ensure that the system can block commutation failure and operate safely and stably within the DC current command value range.

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

[0133] A voltage acquisition module is used to obtain the AC commutation voltage of the high-voltage DC transmission station in real time;

[0134] A DC current command calculation module is used to generate a DC current command value based on a DC current command prediction model obtained through system identification under the current fault when a fault occurs in the high-voltage DC transmission system and if the AC commutation voltage is lower than a set voltage threshold; wherein the DC current command value takes into account the static safety commutation boundary and increases the overshoot to achieve the control goal of preventing commutation failure.

[0135] In a specific embodiment of the present invention, before the DC current command prediction model obtained by system identification under the current fault is used to generate the DC current command value, the method further includes:

[0136] Training the DC current command prediction model;

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

[0138] 1) By simulating the fault, collecting the simulated DC current command value and AC commutation voltage, as well as the DC current measured value and the leading trigger angle measured value;

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

[0140] 3) Based on the training set obtained in step 2), the identification model is trained, and then the transfer function is obtained from the identification model;

[0141] 4) Performing Laplace transform on the simulated DC current command step value and AC commutation voltage step value of the training sample respectively, and substituting them into the transfer function for calculation, to obtain the DC current predicted Laplace transform value and the advanced trigger angle predicted Laplace transform value corresponding to the training sample; performing inverse Laplace transform on the two Laplace transform values ​​respectively, to obtain the DC current predicted value and the advanced trigger angle predicted value corresponding to each training sample;

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

[0143]

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

[0145]

[0146] Among them, a, b, c are the drop value coefficients of each section; G1 and G2 are transfer functions;

[0147] 5) using the DC current prediction value and the leading trigger angle prediction value corresponding to each training sample obtained in step 4), based on the static safe commutation boundary, to obtain the DC current command prediction value corresponding to each training sample;

[0148]

[0149] Where n is the number of segmented line segments; U L为 AC commutation voltage, I ord is the DC current command value; β is the leading trigger angle, β = π-α, where α is the trigger angle; I d is the DC current of the static safety commutation boundary;

[0150] Among them, the static safe commutation boundary is expressed as:

[0151]

[0152] Where, γ is the inverter extinction angle; X c is the commutation reactance, X c =ωL c .

[0153] In a specific embodiment of the present invention, it also includes:

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

[0155] In a specific embodiment of the present invention, it also includes:

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

[0157] In a specific embodiment of the present invention, it also includes:

[0158] After the fault is cleared, the AC commutation voltage gradually increases to a normal level, and the leading trigger angle is adjusted to maintain stable operation of the system.

[0159] This can realize the DC current control characteristics based on static safety boundaries and system identification, accurately and dynamically adjust the current set value under fault conditions, and introduce a DC current rise rate limiting mechanism; in this way, the commutation failure phenomenon can be effectively suppressed and the normal operating state of the system can be quickly restored after a fault.

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

[0161] at least one processor; and a memory communicatively coupled to the at least one processor;

[0162] The memory stores instructions executable by the at least one processor, and the instructions are configured to execute the above-mentioned commutation failure suppression method based on static safety margin and predictive control.

[0163] To implement the above-mentioned embodiment, the fourth aspect of the present invention proposes a computer-readable storage medium, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable the computer to execute the above-mentioned method for suppressing commutation failure based on static safety margin and predictive control.

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

[0165] The computer-readable medium may be included in the electronic device, or may exist independently without being installed in the electronic device. The computer-readable medium carries one or more programs, and when the one or more programs are executed by the electronic device, the electronic device executes a commutation failure suppression method based on static safety margin and predictive control in the above embodiment.

[0166] Computer program code for performing the operations of the present disclosure may be written in one or more programming languages, or a combination thereof, including object-oriented programming languages, such as Java, Smalltalk, C++, and conventional procedural programming languages, such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate 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 a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., through the Internet using an Internet service provider).

[0167] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0168] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In the description of this application, the meaning of "plurality" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0169] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, segment or portion of code that includes one or more executable instructions for implementing the steps of a specific logical function or process, and the scope of the preferred embodiments of the present application includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in the reverse order depending on the functions involved, which should be understood by technicians in the technical field to which the embodiments of the present application belong.

[0170] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute the instructions), or in combination with these instruction execution systems, devices or apparatuses. For the purpose of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in combination with these instruction execution systems, devices or apparatuses. More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk box (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium and then editing, interpreting or otherwise processing in a suitable manner if necessary, and then stored in a computer memory.

[0171] It should be understood that the various parts of the present application can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0172] A person skilled in the art may understand that all or part of the steps in the method for implementing the above-mentioned embodiment may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiment.

[0173] In addition, each functional unit in each embodiment of the present application may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0174] The storage medium mentioned above may be a read-only memory, a magnetic disk or an optical disk, etc. Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limiting the present application. A person of ordinary skill in the art may change, modify, replace and modify the above embodiments within the scope of the present application.

Claims

1. A commutation failure suppression method based on static safety margin and predictive control, characterized in that: include: Obtain the AC commutation voltage of the HVDC transmission station in real time; 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 a DC current command prediction model obtained through system identification under the current fault; wherein the DC current command value takes into account the static safe commutation boundary and increases the overshoot to achieve the control goal of preventing commutation failure.

2. The method according to claim 1, characterized in that Before the DC current command prediction model obtained by system identification under the current fault is used to generate the DC current command value, the method further includes: Training the DC current command prediction model; The training of the DC current instruction prediction model includes: 1) By simulating the fault, collecting the simulated DC current command value and AC commutation voltage, as well as the DC current measured value and the leading trigger angle measured value; 2) Based on the data collected in step 1), the simulated DC current command value and AC commutation voltage at the time of the fault occurrence are used as input, and the DC current measured value and the leading trigger angle measured value at that time are used for fitting and 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 from the identification model; 4) Performing Laplace transform on the simulated DC current command step value and AC commutation voltage step value of the training sample respectively, and substituting them into the transfer function for calculation, to obtain the DC current predicted Laplace transform value and the advanced trigger angle predicted Laplace transform value corresponding to the training sample; performing inverse Laplace transform on the two Laplace transform values ​​respectively, to obtain the DC current predicted value and the advanced trigger angle predicted value corresponding to each training sample; Among them, the current command step value The Laplace transform function of is: AC commutation voltage drop value The Laplace transform function of is: Among them, a, b, c are the drop value coefficients of each section; G1 and G2 are transfer functions; 5) using the DC current prediction value and the leading trigger angle prediction value corresponding to each training sample obtained in step 4), based on the static safe commutation boundary, to obtain the DC current command prediction value corresponding to each training sample; Where n is the number of segmented line segments; U L为 AC commutation voltage, I ord is the DC current command value; β is the leading trigger angle, β = π-α, where α is the trigger angle; I d is the DC current of the static safety commutation boundary; Among them, the static safe commutation boundary is expressed as: Where, γ is the inverter extinction angle; X c is the commutation reactance, X c =ωL c .

3. The method according to claim 2, characterized in that Also includes: When training the DC current command prediction model, the DC current measured value is smoothed to remove noise, and then the transfer function is identified in the discrete time domain, and then the discrete transfer function is converted into a continuous model.

4. The method according to claim 2, characterized in that: Also includes: After the control target is achieved, the AC commutation voltage is restored and the DC current command value is increased to maintain normal commutation.

5. The method according to claim 4, characterized in that Also includes: After the fault is cleared, the AC commutation voltage gradually increases to a normal level, and the leading trigger angle is adjusted to maintain stable operation of the system.

6. A commutation failure suppression device based on static safety margin and predictive control, characterized in that: include: A voltage acquisition module is used to obtain the AC commutation voltage of the high-voltage DC transmission station in real time; A DC current command calculation module is used to generate a DC current command value based on a DC current command prediction model obtained through system identification under the current fault when a fault occurs in the high-voltage DC transmission system and if the AC commutation voltage is lower than a set voltage threshold; wherein the DC current command value takes into account the static safety commutation boundary and increases the overshoot to achieve the control goal of preventing commutation failure.

7. The device according to claim 6, characterized in that Before the DC current command prediction model obtained by system identification under the current fault is used to generate the DC current command value, the method further includes: Training the DC current command prediction model; The training of the DC current instruction prediction model includes: 1) By simulating the fault, collecting the simulated DC current command value and AC commutation voltage, as well as the DC current measured value and the leading trigger angle measured value; 2) Based on the data collected in step 1), the simulated DC current command value and AC commutation voltage at the time of the fault occurrence are used as input, and the DC current measured value and the leading trigger angle measured value at that time are used for fitting and 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 from the identification model; 4) Performing Laplace transform on the simulated DC current command step value and AC commutation voltage step value of the training sample respectively, and substituting them into the transfer function for calculation, to obtain the DC current predicted Laplace transform value and the advanced trigger angle predicted Laplace transform value corresponding to the training sample; performing inverse Laplace transform on the two Laplace transform values ​​respectively, to obtain the DC current predicted value and the advanced trigger angle predicted value corresponding to each training sample; Among them, the current command step value The Laplace transform function of is: AC commutation voltage drop value The Laplace transform function of is: Among them, a, b, c are the drop value coefficients of each section; G1 and G2 are transfer functions; 5) using the DC current prediction value and the leading trigger angle prediction value corresponding to each training sample obtained in step 4), based on the static safe commutation boundary, to obtain the DC current command prediction value corresponding to each training sample; Where n is the number of segmented line segments; U L为 AC commutation voltage, I ord is the DC current command value; β is the leading trigger angle, β = π-α, where α is the trigger angle; I d is the DC current of the static safety commutation boundary; Among them, the static safe commutation boundary is expressed as: Where, γ is the inverter extinction angle; X c is the commutation reactance, X c =ωL c .

8. The device according to claim 7, characterized in that Also includes: When training the DC current command prediction model, the DC current measured value is smoothed to remove noise, and then the transfer function is identified in the discrete time domain, and then the discrete transfer function is converted into a continuous model.

9. The device according to claim 7, characterized in that Also includes: After the control target is achieved, the AC commutation voltage is restored and the DC current command value is increased to maintain normal commutation.

10. The device according to claim 9, characterized in that Also includes: After the fault is cleared, the AC commutation voltage gradually increases to a normal level, and the leading trigger angle is adjusted to maintain stable operation of the system.

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