Zero-sequence circulating current suppression method and device, electronic equipment and storage medium

Abstract

The invention discloses a zero-sequence circulating current suppression method and device, electronic equipment and a storage medium, and is used for solving the problems that a current zero-sequence circulating current suppression method is relatively large in limitation, has performance imbalance and error accumulation defects and is low in calculation efficiency. The method is applied to a grid-connected system formed by connecting a plurality of alternating-current and direct-current sub-grids in parallel. Acquiring real-time three-phase output of the grid-connected system, a candidate voltage vector set and real-time impedance of each AC / DC sub-grid; performing optimization prediction based on each real-time impedance to obtain a predicted zero-sequence circulating current, and performing layered rolling optimization in combination with the candidate voltage vector set and the predicted zero-sequence circulating current to obtain an optimal voltage vector; performing correction prediction based on parameter compensation according to the real-time three-phase output to obtain a corrected zero-sequence circulating current, and performing closed-loop suppression feedback correction on the corrected zero-sequence circulating current based on the predicted zero-sequence circulating current; and according to the optimal voltage vector, generating a PWM driving signal in combination with the dynamically adjusted switching frequency so as to perform zero-sequence circulating current suppression on the grid-connected system.

Description

Technical Field

[0001] This invention relates to the field of AC / DC power grid connection technology, and in particular to a method, apparatus, electronic device, and storage medium for suppressing zero-sequence circulating current. Background Technology

[0002] Zero-sequence circulating current refers to a special circulating current generated in a three-phase circuit due to system asymmetry (such as load imbalance, ground faults, etc.). Zero-sequence circulating current manifests as a symmetrical current within the three-phase currents. It has the same phase and magnitude, forming a zero-sequence symmetrical current loop. Zero-sequence circulating current typically occurs in neutral-grounded systems and can affect the stability of the power system and the safe operation of equipment.

[0003] When AC / DC power grids are connected, zero-sequence circulating currents between converters are mainly caused by the following reasons: First, inconsistent hardware parameters of parallel converters (such as differences in line impedance and switching device characteristics) can lead to zero-sequence voltage imbalance, thus forming a circulating current path. Second, asynchronous control signals or differences in modulation strategies (such as inconsistent carrier phases) can trigger high-frequency zero-sequence circulating currents. In addition, imbalance conditions between the DC and AC sides (such as DC bus voltage fluctuations or AC side asymmetrical faults) can also generate low-frequency zero-sequence circulating currents. Finally, the lack of electrical isolation in the parallel converter topology (such as a common DC bus structure) provides a closed loop for circulating currents.

[0004] For zero-sequence circulating current suppression, the currently used fixed impedance matching model does not consider the dynamic changes in impedance parameters of parallel systems (such as line temperature rise and device aging), which has significant limitations. Traditional MPC (Model Predictive Control) algorithms cannot simultaneously achieve power point tracking accuracy and circulating current suppression requirements, leading to a performance imbalance. Furthermore, current models mainly employ open-loop control, causing model errors to accumulate over time. Additionally, the computational time required by mainstream global optimization methods (especially when multiple subnets are connected in parallel) cannot meet high-frequency control requirements. Moreover, the independent operation of the system's control and energy management layers, with fixed switching frequencies, results in efficiency losses. Summary of the Invention

[0005] This invention provides a zero-sequence circulating current suppression method, apparatus, electronic device, and storage medium, which solves or partially solves the technical problems of current zero-sequence circulating current suppression methods having significant limitations, performance imbalances, error accumulation defects, and low computational efficiency.

[0006] This invention provides a zero-sequence circulating current suppression method, applied to a grid-connected system, wherein the grid-connected system is composed of multiple AC / DC sub-grids connected in parallel; the method includes:

[0007] Obtain the real-time three-phase output, candidate voltage vector set, and real-time impedance of each AC / DC subgrid of the grid-connected system;

[0008] Based on the real-time impedances, optimization prediction is performed to obtain the predicted zero-sequence circulating current. Then, the candidate voltage vector set and the predicted zero-sequence circulating current are combined to perform hierarchical rolling optimization to obtain the optimal voltage vector.

[0009] Based on the real-time three-phase output, a parameter-compensated correction prediction is performed to obtain the corrected zero-sequence circulating current, and the corrected zero-sequence circulating current is then subjected to closed-loop suppression feedback correction based on the predicted zero-sequence circulating current.

[0010] Based on the optimal voltage vector, a PWM drive signal is generated in conjunction with a dynamically adjusted switching frequency to suppress zero-sequence circulating current in the grid-connected system.

[0011] Optionally, the step of optimizing and predicting based on each of the real-time impedances to obtain the predicted zero-sequence circulating current includes:

[0012] Calculate the dynamic impedance matching factor for each of the aforementioned real-time impedances.

[0013] The zero-sequence voltage components of each of the AC / DC subgrids are obtained, and a weighted average is calculated based on each of the real-time impedances, each of the dynamic impedance matching factors, and each of the zero-sequence voltage components to obtain the predicted zero-sequence circulating current.

[0014] Optionally, the step of performing hierarchical rolling optimization by combining the candidate voltage vector set and the predicted zero-sequence circulating current to obtain the optimal voltage vector includes:

[0015] Based on the predicted zero-sequence circulating current, a multi-objective value function is dynamically weighted and calculated by combining power deviation and DC voltage deviation, and the dynamic weight is output.

[0016] The candidate voltage vector set is subjected to rigid constraint screening to remove voltage vectors that do not meet the preset constraint conditions, thereby obtaining an initial voltage vector subset;

[0017] The initial voltage vector subset is optimized by combining the dynamic weights to obtain an optimized voltage vector subset;

[0018] The voltage vectors in the optimized voltage vector subset are verified by time-domain simulation and perturbation test, and the voltage vector with the best performance is selected from the optimized voltage vector subset as the optimal voltage vector.

[0019] Optionally, the real-time three-phase output includes instantaneous values ​​of the three-phase output voltage and instantaneous values ​​of the three-phase output current; the step of performing parameter-compensated correction prediction based on the real-time three-phase output to obtain the corrected zero-sequence circulating current includes:

[0020] Online parameter identification is performed based on the instantaneous values ​​of the three-phase output voltage and the instantaneous values ​​of the three-phase output current to obtain the equivalent load resistance;

[0021] Based on the equivalent load resistance, and combined with the load resistance deviation and parameter sensitivity matrix, zero-sequence current correction prediction is performed to obtain the corrected zero-sequence circulating current.

[0022] Optionally, the step of performing closed-loop suppression feedback correction on the modified zero-sequence circulating current based on the predicted zero-sequence circulating current includes:

[0023] Obtain the measured zero-sequence circulation current of the current period, and calculate the circulation suppression factor based on the measured zero-sequence circulation current and the predicted zero-sequence circulation current;

[0024] Based on the circulation suppression factor, the closed-loop parameters of the modified zero-sequence circulation are corrected to obtain the secondary modified zero-sequence circulation, and the secondary modified zero-sequence circulation is used as the predicted zero-sequence circulation for the next cycle.

[0025] Optionally, generating the PWM drive signal based on the optimal voltage vector and a dynamically adjusted switching frequency includes:

[0026] Based on the optimal voltage vector and combined with the dynamically adjusted switching frequency, a PWM control signal is generated through space vector modulation.

[0027] The PWM control signal is converted into a PWM drive signal by a drive circuit.

[0028] Optionally, the method further includes:

[0029] Obtain the DC bus voltage of the grid-connected system and the optimal voltage vector of the previous cycle;

[0030] For each of the AC / DC subgrids, a generalized virtual voltage vector is synthesized based on all the basic voltage vectors participating in effective vector synthesis within the AC / DC subgrid.

[0031] Using the constraint that the zero-sequence voltage component of each AC / DC subgrid under the generalized virtual voltage vector is zero, a candidate voltage vector set is constructed based on the DC bus voltage, the optimal voltage vector of the previous cycle, and each of the generalized virtual voltage vectors, while also considering the dynamic radius coefficient related to the predicted zero-sequence circulating current.

[0032] The present invention also provides a zero-sequence circulating current suppression device, applied to a grid-connected system, wherein the grid-connected system is composed of multiple AC / DC sub-grids connected in parallel; the device includes:

[0033] The data acquisition unit is used to acquire the real-time three-phase output, candidate voltage vector set, and real-time impedance of each AC / DC subgrid of the grid-connected system.

[0034] The optimal voltage vector determination unit is used to perform optimization prediction based on each of the real-time impedances to obtain the predicted zero-sequence circulating current, and to perform hierarchical rolling optimization by combining the candidate voltage vector set and the predicted zero-sequence circulating current to obtain the optimal voltage vector.

[0035] The zero-sequence circulating current closed-loop correction unit is used to perform parameter-compensated correction prediction based on the real-time three-phase output to obtain the corrected zero-sequence circulating current, and to perform closed-loop suppression feedback correction on the corrected zero-sequence circulating current based on the predicted zero-sequence circulating current.

[0036] The zero-sequence circulating current suppression unit is used to generate a PWM drive signal based on the optimal voltage vector and a dynamically adjusted switching frequency, so as to suppress the zero-sequence circulating current of the grid-connected system based on the PWM drive signal.

[0037] The present invention also provides an electronic device, the device comprising a processor and a memory:

[0038] The memory is used to store program code and transmit the program code to the processor;

[0039] The processor is configured to execute the zero-sequence circulating current suppression method as described above, according to instructions in the program code.

[0040] The present invention also provides a computer-readable storage medium for storing program code for performing the zero-sequence circulating current suppression method as described in any of the preceding claims.

[0041] As can be seen from the above technical solutions, the present invention has the following advantages:

[0042] A method for suppressing zero-sequence circulating current in a grid-connected system is provided. The grid-connected system consists of multiple AC / DC sub-grids connected in parallel. The method may include the following steps:

[0043] The first step is to obtain the real-time three-phase output, candidate voltage vector set, and real-time impedance of each AC / DC subgrid of the grid-connected system as the basis for subsequent calculations.

[0044] The second step involves optimizing and predicting based on various real-time impedances to obtain the predicted zero-sequence circulating current. This is then combined with a candidate voltage vector set and the predicted zero-sequence circulating current for hierarchical rolling optimization to obtain the optimal voltage vector. Therefore, optimizing and predicting based on real-time impedance allows for dynamic correction of the prediction model based on the weight allocation of real-time impedances, resulting in a more accurate predicted zero-sequence circulating current. The hierarchical rolling optimization design for global optimization significantly reduces computational load and improves computational efficiency through hierarchical selection.

[0045] The third step involves performing parameter-compensated correction prediction based on the real-time three-phase output to obtain the corrected zero-sequence circulating current. Then, based on the predicted zero-sequence circulating current, closed-loop suppression feedback correction is applied to the corrected zero-sequence circulating current. Thus, by establishing a closed loop of parameter compensation correction prediction and circulating current suppression feedback correction, a closed-loop parameter correction mechanism is established. This mechanism can dynamically correct model parameters under closed-loop control, solving the problem of model accumulation error under current open-loop control.

[0046] The fourth step involves generating a PWM drive signal based on the optimal voltage vector and a dynamically adjusted switching frequency to suppress zero-sequence circulating current in the grid-connected system. This addresses the efficiency loss caused by the lack of coordination across time scales by establishing cross-scale parameter correlation rules based on the dynamically adjusted switching frequency to achieve dynamic frequency regulation. Furthermore, this is combined with space vector modulation to generate a PWM drive signal, suppressing zero-sequence circulating current in the grid-connected system and achieving coordinated efficiency and performance optimization. Attached Figure Description

[0047] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0048] Figure 1 A flowchart illustrating the steps of a zero-sequence circulating current suppression method applied to a grid-connected system;

[0049] Figure 2 This is a schematic diagram of the overall process for a zero-sequence circulating current suppression method applied to a grid-connected system.

[0050] Figure 3 This is a structural block diagram of a zero-sequence circulating current suppression device applied to a grid-connected system. Detailed Implementation

[0051] This invention provides a zero-sequence circulating current suppression method, apparatus, electronic device, and storage medium to solve or partially solve the technical problems of current zero-sequence circulating current suppression methods, such as significant limitations, performance imbalances, error accumulation, and low computational efficiency.

[0052] To make the objectives, features, and advantages of this invention more apparent and understandable, the technical solutions of the embodiments of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the embodiments described below are only some embodiments of this invention, and not all embodiments. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention.

[0053] As an example, in AC / DC grid interconnection, zero-sequence circulating current between converters is mainly caused by the following reasons: First, inconsistent hardware parameters of parallel converters (such as differences in line impedance and switching device characteristics) lead to zero-sequence voltage imbalance, thus forming a circulating current path. Second, asynchronous control signals or differences in modulation strategies (such as inconsistent carrier phases) can trigger high-frequency zero-sequence circulating current. Furthermore, imbalances between the DC and AC sides (such as DC bus voltage fluctuations or AC side asymmetrical faults) can also generate low-frequency zero-sequence circulating current. Finally, the lack of electrical isolation in the parallel converter topology (such as a common DC bus structure) provides a closed loop for the circulating current.

[0054] For zero-sequence circulating current suppression, the currently used fixed impedance matching model does not consider the dynamic changes in impedance parameters of parallel systems (such as line temperature rise and device aging), which has significant limitations. Traditional MPC algorithms cannot balance power point tracking accuracy and circulating current suppression requirements, leading to performance imbalance. Furthermore, current models mainly employ open-loop control, causing model errors to accumulate over time. Simultaneously, the computational time of mainstream global optimization methods (especially when multiple subnets are connected in parallel) cannot meet high-frequency control requirements. In addition, the system's control and energy management layers operate independently with fixed switching frequencies, resulting in efficiency losses.

[0055] Therefore, one of the core inventive points of this invention is to propose an improved MPC algorithm based on multi-objective virtual vector collaborative optimization to suppress zero-sequence circulating current caused by the parallel connection of multiple AC / DC subgrids in a grid-connected energy storage system. Addressing the limitations of the fixed impedance matching model, a dynamic impedance matching factor is introduced to achieve real-time impedance weight allocation and dynamically correct the prediction model. To address the performance imbalance problem of traditional MPC, an adaptive weight adjustment mechanism is proposed to dynamically allocate target priorities through dynamic weights. To address the computational efficiency problem of global optimization, a three-level funnel rolling optimization structure is designed to reduce computational load and improve computational efficiency through hierarchical screening. To address the cumulative error problem of open-loop control, a closed-loop parameter correction mechanism is established based on online parameter identification for parameter sensitivity compensation and a feedback correction closed loop based on circulating current suppression factors to dynamically correct model parameters and suppress model cumulative error. To address the efficiency loss problem caused by the lack of cross-timescale collaboration, cross-scale parameter association rules are established to achieve dynamic frequency adjustment, and further combined with space vector modulation to achieve efficiency-performance collaborative optimization.

[0056] Reference Figure 1 This diagram illustrates a flowchart of a zero-sequence circulating current suppression method provided by an embodiment of the present invention. The method is applied to a grid-connected system, which is composed of multiple AC / DC sub-grids connected in parallel. Specifically, the method may include the following steps:

[0057] Step 101: Obtain the real-time three-phase output, candidate voltage vector set, and real-time impedance of each AC / DC subgrid of the grid-connected system;

[0058] In practical applications, it is first necessary to obtain relevant data of the grid-connected system as the basis for subsequent calculations. In this step, the real-time three-phase output, candidate voltage vector set, and real-time impedance of each AC / DC subgrid of the grid-connected system are obtained as the basic data.

[0059] In some embodiments, the candidate voltage vector set can be constructed through the following process: obtaining the DC bus voltage of the grid-connected system and the optimal voltage vector of the previous cycle; for each AC / DC subgrid, synthesizing a generalized virtual voltage vector based on all basic voltage vectors participating in effective vector synthesis within the AC / DC subgrid; using the zero-sequence voltage component of each AC / DC subgrid under the generalized virtual voltage vector as a constraint condition, and based on the DC bus voltage, the optimal voltage vector of the previous cycle, and each generalized virtual voltage vector, while also considering the dynamic radius coefficient related to the predicted zero-sequence circulating current, constructing the candidate voltage vector set.

[0060] Specifically, constructing a candidate voltage vector set can be viewed as building a dynamic virtual vector library. The optimal voltage vector from the previous cycle... DC bus voltage As input to this construction process, the candidate voltage vector set As the output of this construction process, a candidate voltage vector set is constructed. The relevant formulas involved are shown below:

[0061] ;

[0062] ;

[0063] Among them, the optimal voltage vector Initial value calculation: ;

[0064] Based on the active power at the initial moment and reactive power Initial current measurement value The reference voltage vector can be calculated using the following formula: The constraints are set as follows: ;

[0065] in, This represents a generalized virtual voltage vector (composed of basic voltage vectors); Represents the virtual vector composition coefficients ( ); This represents the basic voltage vector (such as the six effective vectors of a two-level inverter). Indicates the number of vectors involved in the synthesis; This represents the candidate voltage vector set (i.e., the candidate virtual vector set). Represents the dynamic radius coefficient ( (related to the prediction of zero-sequence circulation). This represents the optimal voltage vector of the previous control cycle.

[0066] Therefore, by constructing a candidate voltage vector set, it is equivalent to designing a virtual vector library with zero-sequence self-cancellation characteristics. (This increases the constraints.) This achieves the elimination of zero-order components at the source.

[0067] Step 102: Optimize and predict based on each of the real-time impedances to obtain the predicted zero-sequence circulating current, and perform hierarchical rolling optimization by combining the candidate voltage vector set and the predicted zero-sequence circulating current to obtain the optimal voltage vector;

[0068] Building upon the previous steps, this step optimizes and predicts based on each real-time impedance to obtain the predicted zero-sequence circulating current. Then, it combines the candidate voltage vector set and the predicted zero-sequence circulating current to perform hierarchical rolling optimization to obtain the optimal voltage vector.

[0069] In some embodiments, the process of optimizing and predicting based on each real-time impedance to obtain the predicted zero-sequence circulating current may specifically include: calculating the dynamic impedance matching factor of each real-time impedance; obtaining the zero-sequence voltage component of each AC / DC subgrid; and calculating the predicted zero-sequence circulating current by weighted averaging based on each real-time impedance, each dynamic impedance matching factor and each zero-sequence voltage component.

[0070] Specifically, the zero-sequence circulating current dynamic prediction process uses the real-time impedance of each subnet. As input, to predict zero-sequence circulation As output.

[0071] The traditional dynamic equation for zero-sequence circulation is shown below:

[0072] ;

[0073] In this embodiment of the invention, the predicted zero-sequence circulating current is optimized by introducing a dynamic impedance matching factor. The optimized predicted zero-sequence circulating current is calculated using the following formula:

[0074] ;

[0075] in, Indicates the first The zero-sequence impedance of each subnet ( ); Indicates the first The zero-sequence equivalent resistance of each subnet; Indicates the first The zero-sequence equivalent inductance of each subnet; Indicates the fundamental angular frequency of the system ( , (for the fundamental frequency) Indicates the first The zero-sequence voltage component of each subnet; Indicates the first The dynamic impedance matching factor of each subnet ( ); This represents the predicted zero-sequence circulation value; This represents the dynamic zero-sequence circulation value.

[0076] Therefore, by introducing a dynamic impedance matching factor, a zero-sequence circulating current prediction model based on dynamic impedance weight allocation is proposed, which can optimize the accuracy of zero-sequence current prediction compared with the traditional zero-sequence circulating current calculation method.

[0077] In some embodiments, the implementation process of obtaining the optimal voltage vector by performing hierarchical rolling optimization in combination with candidate voltage vector sets and predicted zero-sequence circulating current may specifically include: dynamically weighting a multi-objective value function based on the predicted zero-sequence circulating current, combined with power deviation and DC voltage deviation, and outputting dynamic weights; performing rigid constraint screening on the candidate voltage vector set to remove voltage vectors that do not meet the preset constraint conditions, and obtaining an initial voltage vector subset; performing multi-objective optimization on the initial voltage vector subset in combination with dynamic weights to obtain an optimized voltage vector subset; performing time-domain simulation verification and perturbation testing on the voltage vectors in the optimized voltage vector subset, and selecting the voltage vector with the best performance from the optimized voltage vector subset as the optimal voltage vector.

[0078] Specifically, hierarchical rolling optimization mainly includes two key steps: the first is the dynamic weighting process of multi-objective value functions, and the second is the three-level funnel-shaped rolling optimization process.

[0079] Among them, the multi-objective value function dynamic weighting process is used to predict the zero-sequence current. Power deviation DC voltage deviation As input, with dynamic weights As output. Multi-objective value function and dynamic weights The calculation formula is shown below:

[0080] ;

[0081] In the formula, Indicates the first The original weight coefficients of the parameters involved in the calculation.

[0082] Dynamic weights With candidate voltage vector set This will serve as the input to a three-stage funnel-shaped rolling optimization process, outputting the optimal voltage vector through multi-level optimization. .

[0083] The three-level funnel-shaped rolling optimization mainly includes the following three layered processes:

[0084] The first layer of optimization uses rigid constraint filtering. Its processing flow is as follows: first, iterate through... All voltage vectors in the array are checked, and it is determined whether the following dual constraints are satisfied:

[0085] Zero-sequence current constraint: (Reference value:) );

[0086] Voltage change rate constraint: (e.g., 10³V / s);

[0087] in, Indicates the system's rated current value; This indicates the limit of DC bus voltage change rate (e.g., ≤10³V / s).

[0088] Eliminate voltage vectors that do not satisfy the above dual constraints and output an initial subset of voltage vectors. This reduces the dimensionality of the optimization problem in subsequent calculations.

[0089] The second layer of optimization is a multi-objective optimization. Its processing flow is as follows: First, referring to the aforementioned description, the initial voltage vector subset is... Calculate the value function for each voltage vector. Then press Values ​​sorted in ascending order, select the first Candidates ( =5~10) voltage vectors, construct and output an optimized subset of voltage vectors. .

[0090] Through the multi-objective optimization of the second layer, dynamic weights can be applied, that is, through... Achieve dynamic priority allocation for targets. Automatically elevate priority when a power surge is detected. Weighting. When a DC voltage fluctuation exceeds a threshold, It has the highest priority.

[0091] The third layer of optimization is for dynamic performance verification. Its processing flow is as follows: For the optimized voltage vector subset... The voltage vector was verified through time-domain simulation, followed by application robustness perturbation testing. Finally, the voltage vector with the best performance was output as the optimal voltage vector. The time-domain simulation verification includes: using a simplified model to predict the state evolution over the next three control cycles, and checking derived indicators such as transient overshoot and switching losses. The robust disturbance test involves: superimposing a ±20% disturbance on the parameter identification results, and selecting the voltage vector with the best disturbance rejection performance.

[0092] Thus, through layered rolling optimization, on the one hand, an adaptive weight adjustment mechanism was designed to dynamically allocate target priorities through dynamic weights; on the other hand, an optimization structure with reduced computational load was constructed, reducing the dimensions of the optimization problem, lowering computational costs, and improving computational efficiency.

[0093] Step 103: Perform parameter-compensated correction prediction based on the real-time three-phase output to obtain the corrected zero-sequence circulating current, and perform closed-loop suppression feedback correction on the corrected zero-sequence circulating current based on the predicted zero-sequence circulating current.

[0094] Based on the aforementioned steps, this step mainly involves performing parameter-compensated correction prediction based on the real-time three-phase output to obtain the corrected zero-sequence circulating current, and then performing closed-loop suppression feedback correction on the corrected zero-sequence circulating current based on the predicted zero-sequence circulating current.

[0095] In a specific implementation, the real-time three-phase output can further include the instantaneous values ​​of the three-phase output voltage and the three-phase output current. The implementation process for obtaining the corrected zero-sequence circulating current by performing parameter compensation-based correction prediction based on the real-time three-phase output can include: online parameter identification based on the instantaneous values ​​of the three-phase output voltage and the three-phase output current to obtain the equivalent load resistance; and zero-sequence current correction prediction based on the equivalent load resistance, combined with the load resistance deviation and parameter sensitivity matrix, to obtain the corrected zero-sequence circulating current.

[0096] Specifically, the parameter-compensated correction prediction mainly involves online parameter identification and compensation processes. This process uses the instantaneous values ​​of the three-phase output voltage (measured voltage) as the basis for the prediction. Instantaneous value of three-phase output current (actual measured current) As input, the corrected predicted zero-sequence circulation is used. As output, the equivalent load resistance is obtained through online parameter identification based on the following formula:

[0097] ;

[0098] The zero-sequence current correction prediction model based on parameter compensation is shown below:

[0099] ;

[0100] in, Indicates the equivalent load resistance identified online; Indicates the parameter observation time window (e.g., 1 fundamental frequency period); This represents the instantaneous value of the three-phase output voltage; This represents the instantaneous value of the three-phase output current; Indicates the value of the filter inductance; Represents the parameter sensitivity matrix ( ); Indicates load resistance deviation ( ).

[0101] Furthermore, the implementation process of closed-loop suppression feedback correction of the modified zero-sequence circulation based on the predicted zero-sequence circulation may specifically include: obtaining the measured zero-sequence circulation of the current period; calculating the circulation suppression factor based on the measured zero-sequence circulation and the predicted zero-sequence circulation; performing closed-loop parameter correction on the modified zero-sequence circulation based on the circulation suppression factor to obtain the secondary modified zero-sequence circulation; and using the secondary modified zero-sequence circulation as the predicted zero-sequence circulation of the next period.

[0102] Specifically, the closed-loop suppression feedback correction process uses the measured value of the zero-sequence circulating current. Predicted values Corrected predicted current As input, the corrected prediction model parameters As output, the corrected prediction model parameters Corrected zero-sequence circulation for the current period Perform closed-loop parameter correction to obtain the zero-sequence circulation for the next cycle prediction. The relevant calculation formulas are as follows:

[0103] ;

[0104] in, This represents the circulation inhibition factor.

[0105] By combining online parameter identification with zero-sequence current correction prediction, parameter sensitivity compensation for the zero-sequence circulating current can be performed, making the calculated zero-sequence circulating current more closely reflect actual operating conditions. Through the design of a cumulative error suppression mechanism, the circulating current suppression factor is dynamically updated according to the zero-sequence suppression rate of the current cycle's zero-sequence circulating current, used to correct the prediction model for the next cycle, thereby establishing a closed-loop parameter correction mechanism to suppress model cumulative errors.

[0106] Step 104: Based on the optimal voltage vector, a PWM drive signal is generated in combination with the dynamically adjusted switching frequency to suppress zero-sequence circulating current in the grid-connected system.

[0107] This step generates a PWM (Pulse Width Modulation) drive signal based on the optimal voltage vector determined in the previous steps and the dynamically adjusted switching frequency, so as to suppress zero-sequence circulating current in the grid-connected system based on the PWM drive signal.

[0108] For dynamically adjusted switching frequencies, this embodiment of the invention designs a cross-timescale coordination mechanism. This mechanism designs cross-scale parameter association rules based on the energy storage state of charge (SOC), taking the SOC of the energy storage system as the reference. (State of Charge), Reference Switching Frequency (e.g., 10kHz) as input, with dynamically adjusted switching frequency. As output, the calculation formula for the cross-timescale coordination mechanism is as follows:

[0109] ;

[0110] in, Represents the switching frequency time constant ( ); Indicates the control cycle time constant ( ); Indicates the sampling period (e.g., 50μs); Indicates the energy management time constant ( ); Indicates the switching frequency adjustment coefficient (according to) Dynamically adjust performance and efficiency.

[0111] In the above mechanism, Simultaneously affects the control cycle With energy scale This enables cross-scale parameter correlation (cross-layer coupling).

[0112] In a specific implementation, generating a PWM drive signal based on the optimal voltage vector and a dynamically adjusted switching frequency can include: generating a PWM control signal through space vector modulation based on the optimal voltage vector and a dynamically adjusted switching frequency; and converting the PWM control signal into a PWM drive signal through a drive circuit.

[0113] Specifically, this step uses the optimal voltage vector Switching frequency The input is a PWM drive signal, and the output is a PWM control signal. The PWM control signal is generated and output using Space Vector Modulation (SVM) according to the following formula:

[0114] ;

[0115] in, This represents the generated PWM control signal.

[0116] Finally, the PWM control signal can be converted into a PWM drive signal through the drive circuit to suppress zero-sequence circulating current in the grid-connected system. Space vector modulation (SVM) approximates the optimal voltage vector by synthesizing different voltage vectors, thereby obtaining better waveform quality and higher efficiency, achieving synergistic optimization of efficiency and performance.

[0117] By implementing the scheme provided in the embodiments of the present invention, the zero-order inhibition rate is... It exhibits excellent performance in zero-sequence circulation suppression; flux recovery time It has a faster dynamic response capability; when the inductance deviation is ±50%, it has a faster dynamic response capability. Better robustness; shorter single-cycle computation time. This significantly improves computational efficiency.

[0118] In this invention, an improved MPC algorithm based on multi-objective virtual vector collaborative optimization is proposed to suppress zero-sequence circulating current caused by the parallel connection of multiple AC / DC subgrids in a grid-connected energy storage system. To address the limitations of the fixed impedance matching model, a dynamic impedance matching factor is introduced to achieve real-time impedance weight allocation and dynamically correct the prediction model. To address the performance imbalance problem of traditional MPC, an adaptive weight adjustment mechanism is proposed to dynamically allocate target priorities through dynamic weights. To address the computational efficiency problem of global optimization, a three-level funnel rolling optimization structure is designed to reduce computational load and improve computational efficiency through hierarchical screening. To address the cumulative error problem of open-loop control, a closed-loop parameter correction mechanism is established based on parameter sensitivity compensation based on online parameter identification and feedback correction based on circulating current suppression factors to dynamically correct model parameters and suppress model cumulative error. To address the efficiency loss caused by the lack of cross-timescale collaboration, cross-scale parameter association rules are established to achieve dynamic frequency adjustment, and further combined with space vector modulation to achieve efficiency-performance collaborative optimization.

[0119] Compared with traditional methods, the solution provided by this invention achieves a synergistic improvement in zero-sequence circulating current suppression and system stability by constructing a complete technical chain of "physical model prediction → virtual vector generation → multi-objective optimization → parameter closed-loop correction," thereby accelerating dynamic response and improving computational efficiency. Simultaneously, the parameter transfer in each execution step forms a closed loop, meeting real-time control requirements.

[0120] For better explanation, refer to Figure 2This diagram illustrates the overall flow of a zero-sequence circulating current suppression method for grid-connected systems, as provided in an embodiment of the present invention. It should be noted that this embodiment only provides a brief overview of the general flow of zero-sequence circulating current suppression. The specific implementation process of each step can be understood by referring to the relevant content in the foregoing embodiments, and will not be elaborated upon here. It is understood that the present invention does not impose any limitations on this.

[0121] Step 201: Obtain the real-time three-phase output, candidate voltage vector set, real-time impedance and zero-sequence voltage component of each AC / DC subgrid of the grid-connected system;

[0122] Step 202: Calculate the dynamic impedance matching factor for each real-time impedance, and calculate the predicted zero-sequence circulating current by weighted averaging the real-time impedance, dynamic impedance matching factor and zero-sequence voltage component.

[0123] Step 203: Combine the candidate voltage vector set and the predicted zero-sequence circulating current to perform hierarchical rolling optimization based on dynamic weighting and multi-objective optimization using a multi-objective value function to obtain the optimal voltage vector;

[0124] Step 204: Based on the real-time three-phase output, perform online parameter identification to obtain the equivalent load resistance, and based on the equivalent load resistance, combine the load resistance deviation and parameter sensitivity matrix to perform zero-sequence current correction prediction to obtain the corrected zero-sequence circulating current.

[0125] Step 205: Combine the measured zero-sequence circulating current of the current period with the predicted zero-sequence circulating current and perform closed-loop suppression feedback correction on the corrected zero-sequence circulating current based on the second correction of the zero-sequence circulating current.

[0126] Step 206: Based on the optimal voltage vector and the dynamically adjusted switching frequency, a PWM control signal is generated by space vector modulation. The PWM control signal is converted into a PWM drive signal by the drive circuit, and zero-sequence circulating current suppression is performed on the grid-connected system based on the PWM drive signal.

[0127] Reference Figure 3 This diagram illustrates a structural block diagram of a zero-sequence circulating current suppression device provided by an embodiment of the present invention, applied to a grid-connected system, wherein the grid-connected system is composed of multiple AC / DC sub-grids connected in parallel; the device specifically may include:

[0128] The data acquisition unit 301 is used to acquire the real-time three-phase output, candidate voltage vector set, and real-time impedance of each AC / DC subgrid of the grid-connected system.

[0129] The optimal voltage vector determination unit 302 is used to perform optimization prediction based on each of the real-time impedances to obtain the predicted zero-sequence circulating current, and to perform hierarchical rolling optimization by combining the candidate voltage vector set and the predicted zero-sequence circulating current to obtain the optimal voltage vector.

[0130] The zero-sequence circulating current closed-loop correction unit 303 is used to perform parameter compensation-based correction prediction based on the real-time three-phase output to obtain the corrected zero-sequence circulating current, and to perform closed-loop suppression feedback correction on the corrected zero-sequence circulating current based on the predicted zero-sequence circulating current.

[0131] The zero-sequence circulating current suppression unit 304 is used to generate a PWM drive signal based on the optimal voltage vector and the dynamically adjusted switching frequency, so as to suppress the zero-sequence circulating current of the grid-connected system based on the PWM drive signal.

[0132] In one alternative embodiment, the optimal voltage vector determination unit 302 includes:

[0133] The dynamic impedance matching factor calculation unit is used to calculate the dynamic impedance matching factor of each of the real-time impedances respectively.

[0134] The zero-sequence circulating current prediction calculation unit is used to obtain the zero-sequence voltage components of each of the AC / DC sub-grids, and to perform weighted average calculation based on each of the real-time impedances, each of the dynamic impedance matching factors and each of the zero-sequence voltage components to obtain the predicted zero-sequence circulating current.

[0135] In one alternative embodiment, the optimal voltage vector determination unit 302 includes:

[0136] The dynamic weight calculation unit is used to perform dynamic weighted calculation of multi-objective value functions based on the predicted zero-sequence circulating current, combined with power deviation and DC voltage deviation, and output dynamic weights.

[0137] A voltage vector filtering unit is used to perform rigid constraint filtering on the candidate voltage vector set to filter out voltage vectors that do not meet the preset constraint conditions and obtain an initial voltage vector subset.

[0138] A multi-objective optimization unit is used to perform multi-objective optimization on the initial voltage vector subset in combination with the dynamic weights to obtain an optimized voltage vector subset.

[0139] The optimal voltage vector screening unit is used to perform time-domain simulation verification and perturbation testing on the voltage vectors in the optimized voltage vector subset, and select the voltage vector with the best performance from the optimized voltage vector subset as the optimal voltage vector.

[0140] In one optional embodiment, the real-time three-phase output includes instantaneous values ​​of the three-phase output voltage and instantaneous values ​​of the three-phase output current; the zero-sequence circulating current closed-loop correction unit 303 includes:

[0141] An online parameter identification unit is used to perform online parameter identification based on the instantaneous values ​​of the three-phase output voltage and the instantaneous values ​​of the three-phase output current to obtain the equivalent load resistance;

[0142] The zero-sequence current correction prediction unit is used to perform zero-sequence current correction prediction based on the equivalent load resistance, combined with the load resistance deviation and parameter sensitivity matrix, to obtain the corrected zero-sequence circulating current.

[0143] In one optional embodiment, the zero-sequence circulating closed-loop correction unit 303 includes:

[0144] The circulation suppression factor calculation unit is used to obtain the measured zero-sequence circulation of the current period and calculate the circulation suppression factor based on the measured zero-sequence circulation and the predicted zero-sequence circulation.

[0145] The closed-loop parameter correction unit is used to perform closed-loop parameter correction on the corrected zero-sequence circulation based on the circulation suppression factor to obtain the secondary corrected zero-sequence circulation, and use the secondary corrected zero-sequence circulation as the predicted zero-sequence circulation for the next cycle.

[0146] In one alternative embodiment, the zero-sequence circulating current suppression unit 304 includes:

[0147] The PWM control signal generation unit is used to generate a PWM control signal by space vector modulation based on the optimal voltage vector and the dynamically adjusted switching frequency.

[0148] The PWM drive signal conversion unit is used to convert the PWM control signal into a PWM drive signal through a drive circuit.

[0149] In one alternative embodiment, the device further includes:

[0150] The data acquisition subunit is used to acquire the DC bus voltage of the grid-connected system and the optimal voltage vector of the previous cycle.

[0151] A generalized virtual voltage vector synthesis unit is used to synthesize a generalized virtual voltage vector for each of the AC / DC subgrids, based on all the basic voltage vectors that participate in effective vector synthesis within the AC / DC subgrids.

[0152] The candidate voltage vector set construction unit is used to construct a candidate voltage vector set based on the DC bus voltage, the previous cycle optimal voltage vector, and each of the generalized virtual voltage vectors, taking the zero-sequence voltage component of each AC / DC subgrid under the generalized virtual voltage vector as a constraint condition, and considering the dynamic radius coefficient related to the predicted zero-sequence circulating current.

[0153] As the device embodiment is basically similar to the method embodiment, it is described in a relatively simple way. For relevant details, please refer to the description of the method embodiment above.

[0154] This invention also provides an electronic device, which includes a processor and a memory:

[0155] The memory is used to store program code and transfer the program code to the processor;

[0156] The processor is used to execute the zero-sequence circulating current suppression method of any embodiment of the present invention according to the instructions in the program code.

[0157] This invention also provides a computer-readable storage medium for storing program code for executing the zero-sequence circulating current suppression method of any embodiment of this invention.

[0158] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0159] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this invention are all information and data authorized by the user or fully authorized by all parties. Furthermore, the collection, use and processing of related data must comply with the relevant laws, regulations and standards of the relevant countries and regions, and corresponding operation entry points are provided for users to choose to authorize or refuse.

[0160] In the embodiments provided by this invention, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection between devices or units through some interfaces, and may be electrical, mechanical, or other forms.

[0161] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0162] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0163] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0164] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for suppressing zero-sequence circulation, characterized in that, The method is applied to a grid-connected system, which consists of multiple AC / DC sub-grids connected in parallel; the method includes: Obtain the real-time three-phase output, candidate voltage vector set, and real-time impedance of each AC / DC subgrid of the grid-connected system; Based on the real-time impedances, optimization prediction is performed to obtain the predicted zero-sequence circulating current. Then, the candidate voltage vector set and the predicted zero-sequence circulating current are combined to perform hierarchical rolling optimization to obtain the optimal voltage vector. Based on the real-time three-phase output, a parameter-compensated correction prediction is performed to obtain the corrected zero-sequence circulating current, and the corrected zero-sequence circulating current is then subjected to closed-loop suppression feedback correction based on the predicted zero-sequence circulating current. Based on the optimal voltage vector, a PWM drive signal is generated in conjunction with a dynamically adjusted switching frequency to suppress zero-sequence circulating current in the grid-connected system.

2. The zero-sequence circulating current suppression method according to claim 1, characterized in that, The optimization prediction based on each of the real-time impedances to obtain the predicted zero-sequence circulating current includes: Calculate the dynamic impedance matching factor for each of the aforementioned real-time impedances. The zero-sequence voltage components of each of the AC / DC subgrids are obtained, and a weighted average is calculated based on each of the real-time impedances, each of the dynamic impedance matching factors, and each of the zero-sequence voltage components to obtain the predicted zero-sequence circulating current.

3. The zero-sequence circulating current suppression method according to claim 1, characterized in that, The step of combining the candidate voltage vector set and the predicted zero-sequence circulating current to perform hierarchical rolling optimization to obtain the optimal voltage vector includes: Based on the predicted zero-sequence circulating current, a multi-objective value function is dynamically weighted and calculated by combining power deviation and DC voltage deviation, and the dynamic weight is output. The candidate voltage vector set is subjected to rigid constraint screening to remove voltage vectors that do not meet the preset constraint conditions, thereby obtaining an initial voltage vector subset; The initial voltage vector subset is optimized by combining the dynamic weights to obtain an optimized voltage vector subset; The voltage vectors in the optimized voltage vector subset are verified by time-domain simulation and perturbation test, and the voltage vector with the best performance is selected from the optimized voltage vector subset as the optimal voltage vector.

4. The zero-sequence circulating current suppression method according to claim 1, characterized in that, The real-time three-phase output includes instantaneous values ​​of three-phase output voltage and instantaneous values ​​of three-phase output current; the step of performing parameter-compensated correction prediction based on the real-time three-phase output to obtain the corrected zero-sequence circulating current includes: Online parameter identification is performed based on the instantaneous values ​​of the three-phase output voltage and the instantaneous values ​​of the three-phase output current to obtain the equivalent load resistance; Based on the equivalent load resistance, and combined with the load resistance deviation and parameter sensitivity matrix, zero-sequence current correction prediction is performed to obtain the corrected zero-sequence circulating current.

5. The zero-sequence circulating current suppression method according to claim 1, characterized in that, The closed-loop suppression feedback correction of the modified zero-sequence circulation based on the predicted zero-sequence circulation includes: Obtain the measured zero-sequence circulation current of the current period, and calculate the circulation suppression factor based on the measured zero-sequence circulation current and the predicted zero-sequence circulation current; Based on the circulation suppression factor, the closed-loop parameters of the modified zero-sequence circulation are corrected to obtain the secondary modified zero-sequence circulation, and the secondary modified zero-sequence circulation is used as the predicted zero-sequence circulation for the next cycle.

6. The zero-sequence circulating current suppression method according to claim 1, characterized in that, The step of generating a PWM drive signal based on the optimal voltage vector and a dynamically adjusted switching frequency includes: Based on the optimal voltage vector and combined with the dynamically adjusted switching frequency, a PWM control signal is generated through space vector modulation. The PWM control signal is converted into a PWM drive signal by a drive circuit.

7. The zero-sequence circulation suppression method according to any one of claims 1 to 6, characterized in that, Also includes: Obtain the DC bus voltage of the grid-connected system and the optimal voltage vector of the previous cycle; For each of the AC / DC subgrids, a generalized virtual voltage vector is synthesized based on all the basic voltage vectors participating in effective vector synthesis within the AC / DC subgrid. Using the constraint that the zero-sequence voltage component of each AC / DC subgrid under the generalized virtual voltage vector is zero, a candidate voltage vector set is constructed based on the DC bus voltage, the optimal voltage vector of the previous cycle, and each of the generalized virtual voltage vectors, while also considering the dynamic radius coefficient related to the predicted zero-sequence circulating current.

8. A zero-sequence circulating current suppression device, characterized in that, The device is applied to a grid-connected system, which consists of multiple AC / DC sub-grids connected in parallel; the device includes: The data acquisition unit is used to acquire the real-time three-phase output, candidate voltage vector set, and real-time impedance of each AC / DC subgrid of the grid-connected system. The optimal voltage vector determination unit is used to perform optimization prediction based on each of the real-time impedances to obtain the predicted zero-sequence circulating current, and to perform hierarchical rolling optimization by combining the candidate voltage vector set and the predicted zero-sequence circulating current to obtain the optimal voltage vector. The zero-sequence circulating current closed-loop correction unit is used to perform parameter-compensated correction prediction based on the real-time three-phase output to obtain the corrected zero-sequence circulating current, and to perform closed-loop suppression feedback correction on the corrected zero-sequence circulating current based on the predicted zero-sequence circulating current. The zero-sequence circulating current suppression unit is used to generate a PWM drive signal based on the optimal voltage vector and a dynamically adjusted switching frequency, so as to suppress the zero-sequence circulating current of the grid-connected system based on the PWM drive signal.

9. An electronic device, characterized in that, The device includes a processor and a memory: The memory is used to store program code and transmit the program code to the processor; The processor is configured to execute the zero-sequence circulating current suppression method according to any one of claims 1-7 according to the instructions in the program code.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium is used to store program code for executing the zero-sequence circulating current suppression method according to any one of claims 1-7.

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