Multi-harmonic absorption multiplexing of grid-forming converter and method for limiting use of active devices thereof

Abstract

The application discloses a method for multi-harmonic absorption multiplexing and utmost limit use of active devices of a network-constructing type converter. The method comprises the following steps: determining a corresponding target function according to a pre-established active device loss model under a multi-harmonic absorption multiplexing control architecture of the network-constructing type converter; the target function at least comprises an utmost limit use target function of the active device and a harmonic weight target function; based on real-time measurement of active power and reactive power, the utmost limit use target function of the active device and the harmonic weight target function are iteratively solved by using a preset multi-objective optimization algorithm to obtain a target harmonic absorption current instruction; and the network-constructing type converter is controlled for harmonic absorption multiplexing based on the target harmonic absorption current instruction. The time-varying nature of the active working condition of the network-constructing type converter is fully utilized, the additional capacity of the network-constructing type converter is multiplexed to absorb the harmonic of the power grid, the utmost limit use of the active device is realized, the utilization rate of the network-constructing type converter is improved, the harmonic level of the power grid is reduced, and the power quality of the power grid is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of grid-connected technology, and in particular to a grid-forming converter multi-harmonic absorption multiplexing and active device limit use method. BACKGROUND

[0002] In a new power system, a grid-forming converter can distribute various distributed renewable energy and energy storage systems into the grid, and at the same time, the active power output condition of the converter itself changes over time, and in most operating time, it does not reach the rated value or the maximum value, and there is a waste of converter capacity, so effectively multiplexing this part of the converter capacity for grid harmonic absorption has high research value and practical value.

[0003] However, the remaining capacity of the converter is not simply the algebraic addition or subtraction of the number of kW or kVA currently understood in the industry, and for the grid-forming converter, the question of how much capacity is consumed by the harmonic needs to add the loss of the active device caused by the fundamental power and the multiple harmonic power to evaluate whether it has reached the maximum allowed loss and heat dissipation. Under the mixing of multiple harmonic currents, the total loss of the active device of the grid-forming converter is not simply the sum of the loss of each harmonic, and there is a complex coupling relationship between the loss models of each harmonic, which causes the active device to be unable to be fully used. Therefore, how to effectively multiplex the remaining capacity of the converter for harmonic absorption on the grid-forming control architecture, while realizing the limit use of the active device is a problem to be solved. SUMMARY

[0004] The present application provides a grid-forming converter multi-harmonic absorption multiplexing and active device limit use method to solve the problem that the remaining capacity of the converter cannot be effectively multiplexed for harmonic absorption on the grid-forming control architecture, and the active device cannot be fully used.

[0005] According to an aspect of the present application, a grid-forming converter multi-harmonic absorption multiplexing and active device limit use method is provided, which comprises:

[0006] According to the pre-established active device loss model under the grid-forming converter multi-harmonic absorption multiplexing control architecture, a corresponding target function is determined; wherein the target function at least includes: an active device limit use target function and a harmonic weight target function; the grid-forming converter multi-harmonic absorption multiplexing control architecture includes: a basic grid-forming control architecture, a current harmonic component calculation module and a harmonic compensation calculation module;

[0007] Based on the active power and reactive power obtained by real-time measurement, the active device limit use target function and the harmonic weight target function are iteratively solved by using a pre-set multi-objective optimization algorithm, and a target harmonic absorption current instruction is obtained.

[0008] The grid-connected converter is controlled based on the target harmonic absorption current instruction.

[0009] According to another aspect of the present application, there is provided a grid-connected converter multi-harmonic absorption multiplexing and active device full utilization device, comprising:

[0010] A target function determination module is configured to determine a corresponding target function according to a pre-established active device loss model under a grid-connected converter multi-harmonic absorption multiplexing control architecture; wherein the target function at least includes an active device full utilization target function and a harmonic weight target function; the grid-connected converter multi-harmonic absorption multiplexing control architecture includes a basic grid-connected control architecture, a current harmonic component calculation module and a harmonic compensation calculation module.

[0011] An instruction solving module is configured to obtain active power and reactive power through real-time measurement, and solve the active device full utilization target function and the harmonic weight target function through a preset multi-objective optimization algorithm to obtain a target harmonic absorption current instruction.

[0012] A harmonic absorption multiplexing control module is configured to control the grid-connected converter based on the target harmonic absorption current instruction.

[0013] According to another aspect of the present application, there is provided an electronic device, comprising:

[0014] at least one processor; and

[0015] a memory connected to the at least one processor; wherein

[0016] The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to execute the grid-connected converter multi-harmonic absorption multiplexing and active device full utilization method according to any one of the embodiments of the present application.

[0017] According to another aspect of the present application, there is provided a computer readable storage medium storing computer instructions for enabling a processor to execute the grid-connected converter multi-harmonic absorption multiplexing and active device full utilization method according to any one of the embodiments of the present application.

[0018] The technical scheme of the embodiment of the present application determines the corresponding active device limit use target function and harmonic weight target function through the active device loss model constructed under the multi-harmonic absorption multiplexing control architecture of the grid-forming type converter, and then obtains the optimal target harmonic absorption current instruction by iteratively solving the active device limit use target function and the harmonic weight target function after taking the real-time measured active power and reactive power under the current working condition as the input of the preset multi-objective optimization algorithm, and then performs harmonic absorption multiplexing control on the grid-forming type converter based on the target harmonic absorption current instruction, thereby solving the problems that the residual capacity of the converter cannot be effectively multiplexed for harmonic absorption on the grid-forming type control architecture, and the active device cannot be used to the limit, fully utilizing the time-varying nature of the active working condition of the grid-forming type converter, multiplexing the additional capacity to absorb the grid harmonic, so as to realize the limit use of the active device of the grid-forming type converter, improve the utilization rate of the grid-forming type converter, and reduce the grid harmonic level, thereby improving the power quality of the grid.

[0019] It should be understood that the content described in this part is not intended to identify key or important features of the embodiments of the present application, nor is it used to limit the scope of the present application. Other features of the present application will become apparent from the following description. BRIEF DESCRIPTION OF DRAWINGS

[0020] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can also be obtained by those skilled in the art without creative labor.

[0021] Figure 1 is a structural schematic diagram of a multi-harmonic absorption multiplexing control architecture of a grid-forming type converter according to the first embodiment of the present application;

[0022] Figure 2 is a flowchart of a multi-harmonic absorption multiplexing and active device limit use method of a grid-forming type converter according to the first embodiment of the present application;

[0023] Figure 3 is a flowchart of a multi-harmonic absorption multiplexing and active device limit use method of a grid-forming type converter according to the second embodiment of the present application;

[0024] Figure 4 is a flowchart of another multi-harmonic absorption multiplexing and active device limit use method of a grid-forming type converter according to the second embodiment of the present application;

[0025] Figure 5 is a fitness evolution curve according to the second embodiment of the present application;

[0026] Figure 6 is a structural schematic diagram of a grid-connected converter multi-harmonic absorption multiplexing and active device utmost limit use device provided according to an embodiment three of the present application;

[0027] Figure 7 is a structural schematic diagram of an electronic device for implementing a method of grid-connected converter multi-harmonic absorption multiplexing and active device utmost limit use provided by an embodiment of the present application. DETAILED DESCRIPTION

[0028] In order for those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor should fall within the scope of protection of the present application.

[0029] It should be noted that the terms "first", "second", and the like in the specification and claims of the present application and the above-described drawings are used to distinguish similar objects, and do not necessarily have to be used to describe a specific order or sequence. It should be understood that the data thus used can be interchanged under appropriate circumstances, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product, or device that includes a series of steps or units does not have to be limited to only those steps or units clearly listed, but can include other steps or units that are not clearly listed or inherent to these processes, methods, products, or devices.

[0030] Embodiment one

[0031] Figure 1 is a structural schematic diagram of a grid-connected converter multi-harmonic absorption multiplexing control architecture provided by an embodiment one of the present application. As shown in the figure, the grid-connected converter multi-harmonic absorption multiplexing control architecture of the present embodiment includes the following two parts: Figure 1

[0032] (1) Basic grid-connected control architecture:

[0033] Based on the basic grid-connected control architecture, the filter capacitor voltage u c and the grid-side current i2 connected by grid connection can be sampled and input to the instantaneous power calculation module to determine the instantaneous active power P out and the instantaneous reactive power Q out output by the converter; then the instantaneous active power P out and the instantaneous reactive power Q out ​and given preset active power P set and preset reactive power Q set is input to the power ring, and a reference voltage amplitude V ref and a virtual angular frequency ω m is generated by simulating the rotor motion and excitation characteristics of the synchronous generator m is integrated to obtain a reference voltage phase θ ref ; then the reference voltage amplitude V ref and the reference voltage phase θ ref are input to the voltage instruction calculation module to obtain a reference voltage instruction u ref ; the reference voltage instruction u ref is transmitted to the instruction side of the voltage and current double closed loop control module as a fundamental reference voltage to realize basic grid-forming control. Figure 1 , wherein G u is a transfer function of the voltage outer loop controller, and G i is a transfer function of the current inner loop controller.

[0034] (2) Multi-harmonic absorption multiplexing control architecture:

[0035] The grid-side current harmonic component i gh is calculated by inputting the sampled grid-side current i2 into the current harmonic component calculation module, and then the grid-side current harmonic component i gh is subtracted from the input harmonic absorption current instruction i ref.h to generate a harmonic voltage instruction u ref.h through the harmonic compensation calculation module in a closed loop; then the harmonic voltage instruction u ref.h is superimposed with the aforementioned reference voltage instruction u ref , and then voltage and current double closed loop control and pulse width modulation (PWM) are performed, so that the multi-harmonic absorption multiplexing control architecture of the grid-forming converter realizes multi-harmonic absorption multiplexing of the grid-forming converter.

[0036] Based on the multi-harmonic absorption multiplexing control architecture of the grid-forming converter, Figure 2 a flowchart of the multi-harmonic absorption multiplexing of the grid-forming converter and the method for limiting the use of active devices thereof is provided in Embodiment One of the present application. The present embodiment can be applied to the case of limiting the use of active devices of the grid-forming converter for harmonic absorption multiplexing. The method can be executed by a multi-harmonic absorption multiplexing device of the grid-forming converter and a device for limiting the use of active devices thereof. The multi-harmonic absorption multiplexing device of the grid-forming converter and the device for limiting the use of active devices thereof can be realized in the form of hardware and / or software, and can be configured in an electronic device. For example, Figure 2As shown, the embodiment one provides a network-constructed converter multi-harmonic absorption multiplexing and active device limit use method, and specifically includes the following steps:

[0037] In S110, the corresponding target function is determined according to the active device loss model under the network-constructed converter multi-harmonic absorption multiplexing control architecture, wherein the target function at least includes: the active device limit use target function and the harmonic weight target function; the network-constructed converter multi-harmonic absorption multiplexing control architecture includes: the basic network-constructed control architecture, the current harmonic component calculation module and the harmonic compensation calculation module.

[0038] The active device can at least include the electronic components such as the Insulated Gate Bipolar Transistor (IGBT) and the diode in the network-constructed converter. The active device loss model can at least include the conduction loss model and the switching loss model of the active device.

[0039] The target function can be a double optimization target for representing that the active device loss of the network-constructed converter reaches the upper limit and meets the harmonic weight proportion distribution. The target function can at least include: the active device limit use target function and the harmonic weight target function. The active device limit use target function can be used to represent the loss condition of the active device of the network-constructed converter; the harmonic weight target function can be used to represent the harmonic weight proportion distribution condition.

[0040] In the embodiment of the application, the active device loss model can be established based on Figure 1 The network-constructed converter multi-harmonic absorption multiplexing control architecture is constructed, and the IGBT, the diode and other active devices in the network-constructed converter are included. The corresponding active device loss model is established, such as the conduction loss model and the switching loss model of the active device. Meanwhile, the target function with the optimization target that the active device loss reaches the upper limit and meets the harmonic weight proportion distribution is established, wherein the target function at least includes: the active device limit use target function and the harmonic weight target function.

[0041] In S120, the active device limit use target function and the harmonic weight target function are iteratively solved by using the preset multi-objective optimization algorithm based on the real-time measurement obtained active power and reactive power, and the target harmonic absorption current instruction is obtained.

[0042] The preset multi-objective optimization algorithm can be a method for solving the optimization problem of multiple target functions, and the preset multi-objective optimization algorithm can include but is not limited to: the particle swarm optimization algorithm, the genetic algorithm, the differential evolution algorithm and the simulated annealing algorithm, etc.

[0043] The target harmonic absorption current instruction can be an optimal harmonic absorption current instruction determined by a preset multi-target optimization algorithm under the current active working condition of the converter (i.e. Figure 1 ref.h ), that is, the target harmonic absorption current instruction at this time can meet the double optimization targets that the active device loss of the grid-forming converter reaches the upper limit (active limit) and conforms to the proportional distribution of harmonic weights (multi-harmonic absorption). The harmonic absorption current instruction can include the following information: harmonic absorption current amplitude and harmonic absorption current phase.

[0044] In the embodiment of the present application, the active power P out and the reactive power Q out output by the converter under the multi-harmonic absorption multiplexing control architecture of the grid-forming converter can be collected by the grid data acquisition device, and the active power P out and the reactive power Q out are taken as inputs of the preset multi-target optimization algorithm, and the active device limit use target function and the harmonic weight target function are iteratively solved, so as to obtain the target harmonic absorption current instruction that can meet the double optimization targets that the active device loss of the grid-forming converter reaches the upper limit (active limit) and conforms to the proportional distribution of harmonic weights (multi-harmonic absorption). In a specific embodiment, for example, taking the particle swarm optimization algorithm as an example, the active device limit use target function and the harmonic weight target function can be taken as the fitness function of the particle swarm optimization algorithm, and the harmonic absorption current instruction to be optimized is taken as a particle in the particle swarm, and then the active power and the reactive power obtained by real-time measurement and the optimization constraints corresponding to the particle swarm optimization algorithm are used to continuously iterate each particle in the particle swarm, and after the iteration termination condition is met, the final target harmonic absorption current instruction is determined according to the group extremum (global optimal solution) corresponding to the current particle swarm.

[0045] S130, based on the target harmonic absorption current instruction, performing harmonic absorption multiplexing control on the grid-forming converter.

[0046] In the embodiment of the present application, based on the multi-harmonic absorption multiplexing control architecture of the grid-forming converter shown in FIG. Figure 1 , the i ref.h of the determined target harmonic absorption current instruction is subtracted from the grid-side current harmonic component i gh , and then the harmonic voltage instruction u ref.h is generated through the harmonic compensation calculation module in a closed loop; and then the harmonic voltage instruction u ref.h is used to generate the reference voltage instruction u ref ​The voltage-current double-loop control and PWM modulation are carried out, and then the grid-connected converter is controlled to realize multi-harmonic absorption multiplexing. Based on the target harmonic absorption current instruction, the grid-connected converter can be used to absorb multiple harmonics in the grid under the working condition change of active and reactive power, so as to realize the full use of active devices, thereby improving the utilization rate of the grid-connected converter and helping to reduce the harmonic level of the grid.

[0047] The technical scheme of the embodiment of the application determines the corresponding active device full use target function and harmonic weight target function according to the active device loss model constructed under the multi-harmonic absorption multiplexing control architecture of the grid-connected converter, and then obtains the optimal target harmonic absorption current instruction by iteratively solving the active device full use target function and the harmonic weight target function after taking the real-time measured active power and reactive power under the current working condition as the input of the preset multi-objective optimization algorithm. Then, the grid-connected converter is controlled based on the target harmonic absorption current instruction for harmonic absorption multiplexing, which solves the problem that the remaining capacity of the converter cannot be effectively multiplexed for harmonic absorption under the grid-connected control architecture, and the active devices cannot be fully used. The time-varying nature of the active working condition of the grid-connected converter is fully utilized, and the additional capacity is multiplexed to absorb the grid harmonics, so as to realize the full use of the active devices, improve the utilization rate of the grid-connected converter, and reduce the grid harmonic level, thereby improving the power quality of the grid.

[0048] Embodiment two

[0049] Figure 3 A flowchart of a grid-connected converter multi-harmonic absorption multiplexing and active device full use method provided by the embodiment two of the application is based on the above-mentioned embodiments and is further optimized and expanded, and can be combined with each optional technical scheme in the above-mentioned embodiments. As shown in Figure 3 The grid-connected converter multi-harmonic absorption multiplexing and active device full use method provided by the embodiment two specifically includes the following steps:

[0050] S210, an active device loss model under a grid-connected converter multi-harmonic absorption multiplexing control architecture is obtained, and a harmonic weight target function is obtained.

[0051] In the embodiment of the application, the active device loss model under the grid-connected converter multi-harmonic absorption multiplexing control architecture can be obtained from a local or cloud server or other data storage location. Figure 1The active device loss model and the harmonic weight objective function pre-constructed under the multi-harmonic absorption multiplexing control architecture of the middle network type converter, wherein the active device loss model comprises: an IGBT loss model and a diode loss model, and the IGBT loss model can be constructed based on the conduction loss and the switching loss of the IGBT of the converter, and the diode loss model can be constructed based on the conduction loss and the switching loss of the diode of the converter.

[0052] Further, on the basis of the above-mentioned embodiments of the application, the active device loss model can be expressed as:

[0053]

[0054] In the formula, P IGBT is the IGBT loss (model); P condIGBT is the IGBT conduction loss; P sw is the IGBT switching loss; P Diode is the diode loss (model); P condDiode is the diode conduction loss; P rec is the diode switching loss.

[0055] Further, the conduction loss model of the active device, i.e. the IGBT conduction loss P condIGBT and the diode conduction loss P condDiode can be respectively expressed as follows:

[0056]

[0057] In the formula, f(i,j) is a function related to the harmonic order; k is the harmonic order; v CE is the collector-emitter voltage; r CE is the conduction resistance of the IGBT in the amplification state; i ac is the alternating harmonic combination; V CE0 is the on-state voltage drop; f1 is the fundamental frequency; is the phase angle of the kth harmonic absorption current; I k is the amplitude of the kth harmonic absorption current; T0 is the current period; is the power factor angle; ω is the fundamental angular frequency; m is the modulation ratio; I1 is the fundamental current amplitude; is the phase angle of the fundamental current; I i is the amplitude of the ith harmonic absorption current; I j is the amplitude of the jth harmonic current; f sw is the IGBT switching frequency; v F is the diode conduction voltage; R on is the diode conduction resistance.

[0058] Further, the switching loss model of the active device, i.e. the IGBT switching loss Psw and diode switching loss P rec may be expressed as follows, respectively:

[0059]

[0060] In the formula, V DC is a direct current voltage; V nom is a direct current voltage reference value; a, b, c, a', b' and c' are all coefficients.

[0061] Further, on the basis of the above-mentioned embodiments of the application, the harmonic weight objective function can be expressed as follows:

[0062]

[0063] In the formula, Q represents the harmonic weight objective function; k represents the harmonic order; h k represents the kth harmonic importance weight coefficient; I k represents the kth harmonic absorption current amplitude.

[0064] Further, the kth harmonic importance weight coefficient h k may be expressed as:

[0065]

[0066] In the formula, a j is a sensitive factor of the jth harmonic.

[0067] S220, based on the IGBT loss model, the diode loss model and the respective rated losses, determine the corresponding IGBT loss limit use objective function and diode loss limit use objective function as active device limit use objective functions.

[0068] In the embodiments of the application, the corresponding active device limit use objective functions can be determined based on the aforementioned obtained IGBT loss model and diode loss model and the respective rated losses, wherein the active device limit use objective functions can include: IGBT loss limit use objective function and diode loss limit use objective function.

[0069] Further, on the basis of the above-mentioned embodiments of the application, the active device limit use objective function can be expressed as follows:

[0070]

[0071] In the formula, δ1 represents the IGBT loss limit use objective function; P IGBT represents the IGBT loss; P IGBTN represents the IGBT rated loss; δ2 represents the diode loss limit use objective function; PDiode Indicates diode loss; P DiodeN This indicates the rated loss of the diode.

[0072] S230. Obtain the active power and reactive power measured in real time under the multi-harmonic absorption and multiplexing control architecture of the grid-type converter, and determine the corresponding real-time value of the fundamental current by calling the preset fundamental current calculation formula according to the active power and reactive power.

[0073] In this embodiment of the invention, the active power P under the current operating condition of the multi-harmonic absorption and multiplexing control architecture of the grid-type converter can be collected by a power grid data acquisition device. out and reactive power Q out Then, the active power P is determined by calling the following preset fundamental current calculation formula. out and reactive power Q out The corresponding real-time value of the fundamental current I:

[0074]

[0075] In the formula, U is the three-phase line voltage.

[0076] S240. Obtain the optimization constraints and iteration termination conditions corresponding to the particle swarm optimization algorithm.

[0077] The optimization constraint can refer to the conditions used to limit the solution space (i.e., harmonic absorption current command) corresponding to the objective function. In this embodiment, the optimization constraint can be: the loss value of the active device cannot exceed its rated loss, i.e., the IGBT loss P. IGBT It cannot exceed the corresponding IGBT rated loss P IGBTN and diode loss P Diode It cannot exceed the corresponding diode's rated loss P DiodeN .

[0078] The iteration termination condition can refer to the execution termination condition of the preset particle swarm optimization algorithm. The iteration termination condition can include: the number of iterations reaches the preset maximum number of iterations, the fitness value deviation between two iterations reaches the preset stopping tolerance (that is, the difference between the fitness value of the optimal solution after the previous iteration and the fitness value of the optimal solution after the current iteration is less than the preset value), etc.

[0079] In this embodiment of the invention, the optimization constraints and iteration termination conditions corresponding to the particle swarm optimization algorithm to be called later can be obtained from data storage locations such as local or cloud servers.

[0080] Furthermore, based on the above embodiments of the invention, the optimized constraints can be expressed as follows:

[0081]

[0082] S250, taking the harmonic absorption current instruction to be solved as a particle in the particle swarm, and initializing the position and speed corresponding to each particle based on the optimization constraint condition.

[0083] In the embodiment of the present application, the pre-configured particle swarm optimization algorithm can be called, the harmonic absorption current instruction is taken as a particle in the particle swarm, and the initialization operation is performed based on the optimization constraint condition, that is, the population size (the number of particles), the particle dimension (the spatial dimension of particle search, that is, the dimension of the parameters to be optimized), the position of each particle (a solution to the optimization problem to be solved, that is, a certain harmonic absorption current instruction), the speed, the individual extreme value (the individual optimal solution), the preset maximum iteration number, the group extreme value (the global optimal solution) are initialized. The i-th particle in the particle swarm can be expressed as follows:

[0084]

[0085] In the formula, I i is the amplitude of the i-th harmonic absorption current; is the phase of the i-th harmonic absorption current.

[0086] S260, based on the active device limit use target function, the harmonic weight target function and the real-time value of the fundamental current, the adaptive value corresponding to each particle is determined.

[0087] In the embodiment of the present application, the active device limit use target function and the harmonic weight target function can be taken as the fitness function of the preset particle swarm optimization algorithm, and the real-time value of the fundamental current and the harmonic absorption current amplitude and phase corresponding to each particle at the current iteration number are substituted into the above fitness function to obtain the adaptive value corresponding to each particle in this iteration.

[0088] S270, updating the individual extreme value of the corresponding particle and the group extreme value of the particle swarm by using the adaptive value.

[0089] The individual extreme value can refer to the individual optimal solution corresponding to the particle in this iteration. The group extreme value can refer to the global optimal solution corresponding to the particle swarm.

[0090] In the embodiment of the present application, S270 can specifically include:

[0091] If the adaptive value of the particle is greater than the adaptive value corresponding to the individual extreme value of the particle, the individual extreme value of the particle is updated by using the position of the particle in this iteration;

[0092] If the adaptive value of the particle is less than the adaptive value corresponding to the individual extreme value of the particle, the individual extreme value of the particle is kept unchanged in this iteration;

[0093] If the fitness value of the particle is greater than the fitness value corresponding to the group extremum of the particle swarm, the group extremum of the particle swarm is updated by using the position of the particle in the current iteration;

[0094] If the fitness value of the particle is less than the fitness value corresponding to the group extremum of the particle swarm, the group extremum of the particle swarm is kept unchanged in the current iteration.

[0095] It should be understood that the position and speed of the particle in the preset particle swarm optimization algorithm (multi-objective particle swarm optimization algorithm) of the embodiment are still updated according to the method of the single-objective particle swarm optimization algorithm. The difference between the single-objective particle swarm optimization algorithm and the multi-objective particle swarm optimization algorithm is that the final result of the single-objective particle swarm optimization algorithm is only one solution, while the final result of the multi-objective particle swarm optimization algorithm is a Pareto optimal solution set composed of a series of Pareto optimal solutions.

[0096] In the preset particle swarm optimization algorithm of the embodiment, the updating strategy of the individual extremum (individual optimal solution) is that when the new solution generated by the particle is dominated by the old solution, the individual extremum is kept unchanged; when the new solution dominates the old solution, the new solution is used as the individual extremum; and when the new solution and the old solution are not dominated by each other, a solution is randomly selected as the individual extremum.

[0097] The updating strategy of the group extremum (global optimal solution) is that after each iteration, the Pareto optimal solution set calculated with the updated position of the particle is also updated, and a particle is randomly selected from the updated Pareto solution as the group extremum of the next iteration.

[0098] S280, the speed and position of each particle are updated by using the individual extremum and the group extremum, and the number of new iterations is updated.

[0099] In the embodiment of the application, the preconfigured particle speed and position updating formula can be called to update the speed and position of each particle, and the number of iterations is updated.

[0100] Further, on the basis of the above-mentioned embodiment of the application, the particle speed and position updating formula can be expressed as follows:

[0101]

[0102] In the formula, v ij (t) is the jth-dimensional speed component of the ith particle in the tth iteration process; x ij (t) is the jth-dimensional position component of the ith particle in the tth iteration process; ω inertia is an inertia coefficient, used to control the influence of the previous speed of the particle on the current speed, which will affect the global and local search ability of the particle; c1 is an individual learning coefficient; c2 is a global learning coefficient; r1 and r2 are two independent random numbers in the interval [0, 1]; pij (t) is an individual extremum of the i-th particle; p gj (t) is a group extremum of the particle group.

[0103] S290, judge whether the updated iteration number meets the iteration termination condition.

[0104] In the embodiment of the present application, it can be judged whether the iteration number of the current iteration meets the pre-configured iteration termination condition. If yes, S2100 is executed; if no, S2110 is executed.

[0105] S2100, if yes, output the Pareto optimal solution set corresponding to the current iteration number, and determine the target harmonic absorption current instruction in the Pareto optimal solution set according to the preset weight coefficients corresponding to the active device limit use objective function and the harmonic weight objective function.

[0106] In the embodiment of the present application, if the iteration termination condition is met, the Pareto optimal solution set corresponding to the current iteration number is directly output, and the best global optimal solution, i.e. the final target harmonic absorption current instruction, is selected from the above-mentioned Pareto optimal solution set based on the preset weight coefficients corresponding to the active device limit use objective function and the harmonic weight objective function respectively.

[0107] Further, in S2100, the target harmonic absorption current instruction is determined in the Pareto optimal solution set according to the preset weight coefficients corresponding to the active device limit use objective function and the harmonic weight objective function, which specifically includes the following steps:

[0108] A, determine the first fitness value of the active device limit use objective function corresponding to each Pareto optimal solution in the Pareto optimal solution set, and the second fitness value of the harmonic weight objective function;

[0109] B, for each Pareto optimal solution, respectively determine the first product between the first fitness value and the corresponding first preset weight coefficient, and the second product between the second fitness value and the corresponding second preset weight coefficient, and take the sum of the first product and the second product as the target function weight value;

[0110] C, traverse the target function weight value corresponding to each Pareto optimal solution, and take the corresponding Pareto optimal solution with the maximum target function weight value as the target harmonic absorption current instruction.

[0111] S2110, if no, return to execute the step of determining the fitness value corresponding to each particle based on the active device limit use objective function, the harmonic weight objective function and the real-time value of the fundamental current.

[0112] In the embodiment of the present application, if the iteration termination condition is not met, the steps in S260 are returned to execute the next iteration process of the optimization algorithm.

[0113] S2120, based on the target harmonic absorption current instruction, performing harmonic absorption multiplexing control on the grid-connected converter.

[0114] Figure 4 Another flowchart of the grid-connected converter multi-harmonic absorption multiplexing and the limited use method of the active device thereof provided in Embodiment Two of the present application is shown in FIG. 6. Figure 4 The method mainly includes the following steps:

[0115] 1. Establishing a grid-connected converter multi-harmonic absorption multiplexing control architecture of the grid-connected converter;

[0116] 2. Establishing an active device loss model under the working condition of the grid-connected converter output containing a multi-harmonic combination, wherein the real-time value of the fundamental harmonic current and the harmonic absorption current are inputs, and the active device loss power value is output;

[0117] 3. Calculating the real-time value of the fundamental harmonic current according to the real-time active power and reactive power obtained by measurement, inputting the real-time value into the particle swarm calculation module, and iteratively solving the harmonic absorption current instruction;

[0118] 4. Based on the multi-harmonic current combination input of the current iteration, the active device loss of the grid-connected converter is calculated through the active device loss model in each iteration of the particle swarm calculation module;

[0119] 5. The combination of the multi-harmonic current absorption instruction value (i.e., the target harmonic absorption current instruction) reaching the upper limit of the active device loss of the grid-connected converter and meeting the double optimization objectives of the harmonic weight proportion allocation is obtained through the particle swarm iteration calculation;

[0120] 6. Based on the determined target harmonic absorption current instruction, performing harmonic absorption multiplexing control on the converter.

[0121] It should be noted that, under the condition of a larger grid harmonic current distribution, the use of the dynamic surplus capacity of the grid-connected converter to multiplex and absorb the grid harmonic is based on the condition that the grid harmonic can be fully compensated.

[0122] The technical scheme of the embodiment of the application determines the corresponding IGBT loss limit use target function, diode loss limit use target function and harmonic weight target function according to the IGBT loss model and diode loss model constructed under the multi-harmonic absorption multiplexing control architecture of the network-constructing type converter, then takes the fundamental wave current real-time value and harmonic absorption current instruction determined under the current working condition as the input of the particle swarm optimization algorithm, and obtains the optimal target harmonic absorption current instruction after iterative solving of the active device loss limit use target function and the harmonic weight target function, and then performs harmonic absorption multiplexing control on the network-constructing type converter based on the target harmonic absorption current instruction, solves the problems that the residual capacity of the converter cannot be effectively multiplexed for harmonic absorption on the network-constructing type control architecture, and the active device cannot be used to the limit, fully utilizes the time-varying nature of the active working condition of the network-constructing type converter, multiplexes the additional capacity to absorb the grid harmonic, so as to realize the limit use of the active device of the network-constructing type converter, improves the utilization rate of the network-constructing type converter, and reduces the grid harmonic level, thereby improving the power quality of the grid.

[0123] The specific derivation process of the IGBT loss P IGBT and the diode loss P Diode is given below.

[0124] The instantaneous conduction loss of the IGBT is:

[0125]

[0126] In the formula, v CE is the collector-emitter voltage; r CE is the conduction resistance of the IGBT in the amplification state; V CE0 is the on-state voltage drop; i ac is the alternating current harmonic combination; k is the harmonic order; I k is the kth harmonic absorption current amplitude; f1 is the fundamental wave frequency; is the phase angle of the kth harmonic absorption current.

[0127] According to the instantaneous loss calculation:

[0128]

[0129] In the formula, τ(t) is the duty cycle that changes with time.

[0130] Since the harmonics existing in the grid are mostly 6k±1 order harmonics, when the low-order harmonic current and the fundamental wave current are mixed and output on the alternating current side of the converter, the current flowing in the active device is:

[0131]

[0132] Based on the current flowing in the active device, the average conduction loss of the IGBT can be obtained as follows:

[0133]

[0134] where f(i,j) is a function of harmonic order, which can be expressed as:

[0135]

[0136] The switching loss of IGBT can be expressed as a quadratic function as follows:

[0137]

[0138] where V is the DC voltage; V is the DC voltage reference value; the coefficients a, b and c can be obtained by curve fitting. DC nom

[0139] For a millisecond-level pulse, the output current i can be regarded as a constant, and the instantaneous switching loss of IGBT can be expressed as:

[0140]

[0141] Further, the average switching loss of IGBT is:

[0142]

[0143] Therefore, the total loss P of IGBT can be expressed as: IGBT

[0144]

[0145] Similarly, the total loss P of diode can be expressed as: Diode

[0146]

[0147] In order for those skilled in the art to better understand the embodiments of the present application, the following will illustrate the network configuration type converter multi-harmonic absorption multiplexing and the active device limit use method in the embodiments of the present application through specific examples. Taking a three-phase line voltage 380V network configuration type converter as an example, the measured real-time active power P is 6.37kW, the real-time reactive power Q is 2.4kVar. That is, out out

[0148]

[0149] The calculated power factor of the power grid is equal to 0.938, and the real-time value of the fundamental current is 18A.

[0150] ​​​​​​By querying the IGBT data manual, the loss rating P at room temperature 25℃ is obtained tot =250W, and the switching loss function with current change is:

[0151] E sw =4.88*10 -4 i 2 +0.021i+0.07

[0152] After particle swarm optimization iteration calculation, the amplitude and phase of each harmonic absorption current can be obtained, and the corresponding fitness evolution curve is as shown in Figure 5 .

[0153] According to the iteration optimization result, when the amplitude and phase of each harmonic absorption current meet the following table, the active device can be used as much as possible.

[0154] Absorbed current harmonic order Amplitude Phase 5 35.7301 -2.7550 7 13.6529 -0.2974 11 10.9366 1.4766 13 10.6495 2.0917 17 11.4468 -1.3798

[0155] Example Three

[0156] Figure 6 A structure schematic diagram of a network type converter multi-harmonic absorption multiplexing and active device full use device provided for the third embodiment of the application is shown in Figure 6 . The device includes:

[0157] A target function determination module 31 is configured to determine a corresponding target function according to a pre-established active device loss model under a network type converter multi-harmonic absorption multiplexing control architecture; wherein the target function at least includes an active device full use target function and a harmonic weight target function; the network type converter multi-harmonic absorption multiplexing control architecture includes a basic network type control architecture, a current harmonic component calculation module and a harmonic compensation calculation module.

[0158] An instruction solving module 32 is configured to obtain active power and reactive power by real-time measurement, and to use a pre-set multi-objective optimization algorithm to iteratively solve the active device full use target function and the harmonic weight target function, so as to obtain a target harmonic absorption current instruction.

[0159] A harmonic absorption multiplexing control module 33 is configured to perform harmonic absorption multiplexing control on the network type converter based on the target harmonic absorption current instruction.

[0160] The technical scheme of the embodiment of the application determines the corresponding active device limit use target function and the harmonic weight target function through the active device loss model constructed under the multi-harmonic absorption multiplexing control architecture of the grid-forming type converter, takes the active power and the reactive power obtained through real-time measurement under the current working condition as the input of the preset multi-objective optimization algorithm, and obtains the optimal target harmonic absorption current instruction after iteratively solving the active device limit use target function and the harmonic weight target function. Then, the grid-forming type converter is controlled for harmonic absorption based on the target harmonic absorption current instruction, thereby solving the problem that the residual capacity of the converter cannot be effectively multiplexed for harmonic absorption under the grid-forming type control architecture, and the active device cannot be used to the limit. The time-varying nature of the active power working condition of the grid-forming type converter is fully utilized, the additional capacity thereof is multiplexed to absorb the grid harmonic, the limit use of the active device is realized, the utilization rate of the grid-forming type converter is improved, the grid harmonic level is reduced, and thus the power quality of the grid is improved.

[0161] Further, on the basis of the above-mentioned embodiment of the application, the target function determination module 31 comprises:

[0162] The active device loss model and the harmonic weight target function obtaining unit is configured to obtain the active device loss model under the multi-harmonic absorption multiplexing control architecture of the grid-forming type converter, and obtain the pre-configured harmonic weight target function; wherein the active device loss model at least comprises: an IGBT loss model and a diode loss model.

[0163] The active device limit use target function determination unit is configured to determine the corresponding IGBT loss limit use target function and the diode loss limit use target function as the active device limit use target function based on the IGBT loss model, the diode loss model and the corresponding rated loss.

[0164] Further, on the basis of the above-mentioned embodiment of the application, the preset multi-objective optimization algorithm at least comprises: a particle swarm optimization algorithm; correspondingly, the instruction solving module 32 comprises:

[0165] The fundamental wave current real-time value determination unit is configured to obtain the active power and the reactive power obtained through real-time measurement under the multi-harmonic absorption multiplexing control architecture of the grid-forming type converter, and determine the corresponding fundamental wave current real-time value according to the active power and the reactive power by calling the preset fundamental wave current calculation formula.

[0166] The condition obtaining unit is configured to obtain the optimization constraint condition and the iteration termination condition corresponding to the particle swarm optimization algorithm.

[0167] The initialization unit is configured to take the harmonic absorption current instruction to be solved as a particle in the particle swarm, and initialize the position and the speed corresponding to each particle based on the optimization constraint condition.

[0168] An adaptation value determination unit is configured to determine an adaptation value corresponding to each particle based on the active device limit utilization target function, the harmonic weight target function, and the real-time fundamental current value;

[0169] An extreme value updating unit is configured to update an individual extreme value of the corresponding particle and a group extreme value of the particle group by using the adaptation value;

[0170] An updating unit is configured to update the speed and position of each particle and the number of new iterations by using the individual extreme value and the group extreme value;

[0171] A judging unit is configured to judge whether the updated number of iterations meets an iteration termination condition;

[0172] A first processing unit is configured to, if yes, output a corresponding Pareto optimal solution set at the current number of iterations, and determine a target harmonic absorption current instruction in the Pareto optimal solution set according to preset weight coefficients corresponding to the active device limit utilization target function and the harmonic weight target function;

[0173] A second processing unit is configured to, if no, return to execute the step of determining the adaptation value corresponding to each particle based on the active device limit utilization target function, the harmonic weight target function, and the real-time fundamental current value.

[0174] Further, on the basis of the above-mentioned embodiments, the extreme value updating unit is specifically configured to:

[0175] If the adaptation value of the particle is greater than the adaptation value corresponding to the individual extreme value of the particle, the individual extreme value of the particle is updated by using the position of the particle in the current iteration;

[0176] If the adaptation value of the particle is less than the adaptation value corresponding to the individual extreme value of the particle, the individual extreme value of the particle is kept unchanged in the current iteration;

[0177] If the adaptation value of the particle is greater than the adaptation value corresponding to the group extreme value of the particle group, the group extreme value of the particle group is updated by using the position of the particle in the current iteration;

[0178] If the adaptation value of the particle is less than the adaptation value corresponding to the group extreme value of the particle group, the group extreme value of the particle group is kept unchanged in the current iteration.

[0179] Further, on the basis of the above-mentioned embodiments, the target harmonic absorption current instruction is determined in the Pareto optimal solution set according to preset weight coefficients corresponding to the active device limit utilization target function and the harmonic weight target function, including:

[0180] determining a first fitness value of the active device limit use target function corresponding to each Pareto optimal solution in the Pareto optimal solution set, and a second fitness value of the harmonic weight target function corresponding to each Pareto optimal solution;

[0181] For each Pareto optimal solution, a first product between the first fitness value and a corresponding first preset weight coefficient, and a second product between the second fitness value and a corresponding second preset weight coefficient are determined respectively, and a sum of the first product and the second product is taken as a target function weight value;

[0182] The target function weight value corresponding to each Pareto optimal solution is traversed, and a corresponding Pareto optimal solution with the maximum target function weight value is taken as a target harmonic absorption current instruction.

[0183] Further, on the basis of the above-mentioned embodiments of the application, the active device limit use target function is expressed as:

[0184]

[0185] Wherein, δ1 represents the IGBT loss limit use target function; P IGBT represents the IGBT loss; P IGBTN represents the IGBT rated loss; δ2 represents the diode loss limit use target function; P Diode represents the diode loss; P DiodeN represents the diode rated loss;

[0186] The harmonic weight target function is expressed as:

[0187]

[0188] Wherein, Q represents the harmonic weight target function; k represents the harmonic order; h k represents the k-th harmonic importance weight coefficient; I k represents the k-th harmonic absorption current amplitude.

[0189] Further, on the basis of the above-mentioned embodiments of the application, the IGBT loss model is constructed based on the conduction loss and switching loss of the converter IGBT; and the diode loss model is constructed based on the conduction loss and switching loss of the converter diode.

[0190] The network-constructing type converter multi-harmonic absorption multiplexing and active device limit use device provided in the embodiments of the application can perform the network-constructing type converter multi-harmonic absorption multiplexing and active device limit use method provided in any of the embodiments of the application, and has the corresponding function modules and beneficial effects of performing the method.

[0191] Embodiment four

[0192] Figure 7A structural diagram of an electronic device 40 that can be used to implement embodiments of the present application is shown. The electronic device is intended to represent various forms of digital computers, such as laptops, desktops, tablets, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device can also represent various forms of mobile devices such as personal digital assistants, cellular telephones, smartphones, wearable devices (e.g., headsets, glasses, watches, etc.), and other similar computing devices. The components shown here, their connections and relationships, and their functions, are meant to be examples only, and are not intended to limit the implementations of the present application described and / or claimed in this document.

[0193] As shown in Figure 7 The electronic device 40 includes at least one processor 41, and a memory, such as a read-only memory (ROM) 42, a random access memory (RAM) 43, etc., connected to the at least one processor 41 in communication, where the memory stores computer programs executable by the at least one processor. The processor 41 can perform various appropriate actions and processes according to the computer programs stored in the read-only memory (ROM) 42 or loaded into the random access memory (RAM) 43 from the storage unit 48. In the RAM 43, various programs and data required for the operation of the electronic device 40 can also be stored. The processor 41, the ROM 42, and the RAM 43 are connected to each other through a bus 44. An input / output (I / O) interface 45 is also connected to the bus 44.

[0194] Various components in the electronic device 40 are connected to the I / O interface 45, including an input unit 46, such as a keyboard, a mouse, etc., an output unit 47, such as various types of displays, speakers, etc., a storage unit 48, such as a magnetic disk, an optical disk, etc., and a communication unit 49, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 49 allows the electronic device 40 to exchange information / data with other devices through a computer network, such as the Internet, and / or various telecommunications networks.

[0195] The processor 41 can be various general and / or special-purpose processing components with processing and computing capabilities. Some examples of the processor 41 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 41 performs various methods and processes described above, such as the network-forming converter multi-harmonic absorption multiplexing and active device sparing method.

[0196] In some embodiments, the networked converter multi-harmonic absorption multiplexing and active device utilization method can be implemented as a computer program tangibly embodied in a computer readable storage medium, e.g., storage unit 48. In some embodiments, some or all of the computer program can be loaded and / or installed onto electronic device 40 via, e.g., ROM 42 and / or communication unit 49. When the computer program is loaded onto RAM 43 and executed by processor 41, one or more of the steps of the networked converter multi-harmonic absorption multiplexing and active device utilization method described above can be performed. Alternatively, in other embodiments, processor 41 can be configured to perform the networked converter multi-harmonic absorption multiplexing and active device utilization method by way of other any suitable means (e.g., by way of firmware).

[0197] Various implementations of the systems and techniques described above can be realized in digital electronic circuitry, integrated circuitry, a field programmable gate array (FPGA), an application specific integrated circuit (ASIC), a system on a chip (SOC), a programmable logic device (PLD), a computer hardware, firmware, software, and / or combinations thereof. These various implementations can include implementation in one or more computer programs that are executable and / or interpretable on a programmable system including at least one programmable processor, which can be special or general purpose, coupled to receive data and instructions from, and to transmit data and instructions to, a storage system, at least one input device, and at least one output device.

[0198] Computer programs used to implement the methods of the application can be written in any combination of one or more programming languages. These computer programs can be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the computer program, when executed by the processor of the machine, implements the functions / acts specified in the flowcharts and / or block diagrams. The computer program can be executed entirely on a machine, partially on a machine, partially on a machine and partially on a remote machine or entirely on a remote machine or server.

[0199] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0200] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0201] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0202] The computing system can include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system, to solve the defects of large management difficulty and weak business scalability in traditional physical host and VPS service.

[0203] It should be understood that the various forms of flow shown above can be reordered, added to, or have steps deleted. For example, the steps described in the present application can be performed in parallel, in series, or in a different order, as long as the desired results of the technical solutions of the present application can be achieved, and this is not limited herein.

[0204] The above detailed description does not constitute a limitation on the protection scope of the present application. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent replacements, and improvements made within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. A method for networked converter multi-harmonic absorption multiplexing and active device per-unit usage, characterized by, The method comprises: According to the pre-established active device loss model under the multi-harmonic absorption multiplexing control architecture of the grid-forming converter, a corresponding target function is determined; wherein the target function at least includes: active device limit use target function and harmonic weight target function; the multi-harmonic absorption multiplexing control architecture of the grid-forming converter includes: basic grid-forming control architecture, current harmonic component calculation module and harmonic compensation calculation module; Based on the real-time measurement obtained active power and reactive power, the preset multi-objective optimization algorithm is used to iteratively solve the active device limit use target function and the harmonic weight target function, and the target harmonic absorption current instruction is obtained; Based on the target harmonic absorption current instruction, the grid-forming converter is controlled for harmonic absorption multiplexing; Wherein, according to the pre-established active device loss model under the multi-harmonic absorption multiplexing control architecture of the grid-forming converter, the corresponding target function is determined, including: Obtain the pre-established active device loss model under the multi-harmonic absorption multiplexing control architecture of the grid-forming converter, and obtain the pre-configured harmonic weight target function; wherein the active device loss model at least includes: IGBT loss model and diode loss model; Based on the IGBT loss model, the diode loss model and the corresponding rated loss respectively, the corresponding IGBT loss limit use target function and diode loss limit use target function are determined as the active device limit use target function; The active device limit use target function is expressed as: ； wherein, represents the IGBT depletion limit usage objective function; represents IGBT depletion; represents IGBT rated depletion; represents the diode depletion limit usage objective function; represents diode depletion; represents diode rated depletion; The harmonic weight target function is expressed as: ； wherein Q represents the harmonic weight objective function; k represents the harmonic order; represents the kth harmonic importance weight coefficient; represents the kth harmonic absorption current amplitude.

2. The method of claim 1, wherein, The preset multi-objective optimization algorithm at least includes: particle swarm optimization algorithm; Based on the real-time measurement obtained active power and reactive power, the preset multi-objective optimization algorithm is used to iteratively solve the active device limit use target function and the harmonic weight target function, and the target harmonic absorption current instruction is obtained, including: Obtain the real-time measurement obtained active power and reactive power under the multi-harmonic absorption multiplexing control architecture of the grid-forming converter, and determine the corresponding fundamental current real-time value according to the preset fundamental current calculation formula of the active power and the reactive power; Obtain the optimization constraint condition and the iteration termination condition corresponding to the particle swarm optimization algorithm; The to-be-solved harmonic absorption current instruction is taken as a particle in the particle swarm, and the position and speed corresponding to each particle are initialized based on the optimization constraint condition; Based on the active device limit use target function, the harmonic weight target function and the fundamental current real-time value, the fitness value corresponding to each particle is determined; The individual extreme value of the corresponding particle and the group extreme value of the particle swarm are updated by using the fitness value; The speed and position of each particle and the new iteration number are updated by using the individual extreme value and the group extreme value; Determine whether the updated iteration number meets the iteration termination condition; If yes, output the corresponding Pareto optimal solution set at the current iteration number, and determine the target harmonic absorption current instruction in the Pareto optimal solution set according to the preset weight coefficients corresponding to the active device limit use target function and the harmonic weight target function. If no, return to the step of determining the fitness value corresponding to each particle based on the active device limit use target function, the harmonic weight target function, and the real-time value of the fundamental wave current.

3. The method of claim 2, wherein, The updating of the individual extreme value of the corresponding particle and the group extreme value of the particle group by using the fitness value comprises: If the fitness value of the particle is greater than the fitness value corresponding to the individual extreme value of the particle, the individual extreme value of the particle is updated by using the position of the particle in the current iteration; If the fitness value of the particle is less than the fitness value corresponding to the individual extreme value of the particle, the individual extreme value of the particle is kept unchanged in the current iteration; If the fitness value of the particle is greater than the fitness value corresponding to the group extreme value of the particle group, the group extreme value of the particle group is updated by using the position of the particle in the current iteration; If the fitness value of the particle is less than the fitness value corresponding to the group extreme value of the particle group, the group extreme value of the particle group is kept unchanged in the current iteration.

4. The method of claim 2, wherein, The determination of the target harmonic absorption current instruction in the Pareto optimal solution set according to the preset weight coefficients corresponding to the active device limit use target function and the harmonic weight target function comprises: determining the first fitness value of the active device limit use target function and the second fitness value of the harmonic weight target function corresponding to each Pareto optimal solution in the Pareto optimal solution set; determining the first product between the first fitness value and the corresponding first preset weight coefficient and the second product between the second fitness value and the corresponding second preset weight coefficient for each Pareto optimal solution, and taking the sum of the first product and the second product as a target function weight value; traversing the target function weight values corresponding to each Pareto optimal solution, and taking the corresponding Pareto optimal solution with the maximum target function weight value as the target harmonic absorption current instruction.

5. The method of claim 1, wherein, The IGBT loss model is constructed based on the conduction loss and switching loss of the converter IGBT, and the diode loss model is constructed based on the conduction loss and switching loss of the converter diode.

6. A networked converter multi-harmonic absorption multiplexing and active device permissive use apparatus, characterized in that, The device comprises: a target function determination module configured to determine a corresponding target function according to a pre-established active device loss model under a multi-harmonic absorption multiplexing control architecture of a grid-forming converter; wherein the target function at least comprises an active device limit use target function and a harmonic weight target function; and the multi-harmonic absorption multiplexing control architecture of the grid-forming converter comprises a basic grid-forming control architecture, a current harmonic component calculation module, and a harmonic compensation calculation module. The instruction solving module is configured to, based on the active power and the reactive power obtained by real-time measurement, utilize a preset multi-objective optimization algorithm to iteratively solve the active device limit use objective function and the harmonic weight objective function, and obtain a target harmonic absorption current instruction. The harmonic absorption multiplexing control module is configured to perform harmonic absorption multiplexing control on the networked converter based on the target harmonic absorption current instruction. The target function determination module includes: An active device loss model and harmonic weight objective function acquisition unit is configured to acquire a pre-established active device loss model under the networked converter multi-harmonic absorption multiplexing control architecture, and acquire a pre-configured harmonic weight objective function. The active device loss model at least includes an IGBT loss model and a diode loss model. An active device limit use objective function determination unit is configured to determine, based on the IGBT loss model, the diode loss model, and the respective rated loss, a corresponding IGBT loss limit use objective function and a diode loss limit use objective function as the active device limit use objective function. The active device limit use objective function is expressed as: ； wherein, represents the IGBT depletion limit usage objective function; represents IGBT depletion; represents IGBT rated depletion; represents the diode depletion limit usage objective function; represents diode depletion; represents diode rated depletion; The harmonic weight objective function is expressed as: ； wherein Q represents the harmonic weight objective function; k represents the harmonic order; represents the kth harmonic importance weight coefficient; represents the kth harmonic absorption current amplitude.

7. An electronic device, comprising: The electronic device includes: at least one processor; and a memory connected with the at least one processor in communication; wherein The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to execute the networked converter multi-harmonic absorption multiplexing and active device limit use method of any one of claims 1-5.

8. A computer-readable storage medium, characterized in that, The computer readable storage medium stores computer instructions for causing the processor to execute the networked converter multi-harmonic absorption multiplexing and active device limit use method of any one of claims 1-5.

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