A method and system for distributed harmonic regulation in power distribution networks based on photovoltaic converters

Abstract

This invention relates to the field of power grid control technology, and particularly to a distributed harmonic adjustment method and system for distribution networks based on photovoltaic (PV) converters. The method includes: acquiring and preprocessing historical operating data of each node in the distribution network, analyzing and constructing typical operating scenarios; measuring the output voltage and current of each PV converter, and determining a harmonic compensation control architecture based on virtual harmonic conductance; determining power flow constraints and PV inverter constraints based on line parameters, and constructing a multi-objective optimization model with the objectives of minimizing global harmonic distortion rate and network active power loss; solving the multi-objective optimization model according to different typical operating scenarios, developing offline control tables, determining the harmonic compensation output of each PV converter in each scenario, and adjusting the compensation commands of each PV converter online based on the actual mitigation effect. This method can fully utilize the remaining capacity of PV converters and achieve coordinated control between multiple devices through offline optimization.

Description

Technical Field

[0001] This invention relates to the field of power grid control technology, and in particular to a method and system for distributed harmonic regulation of distribution networks based on photovoltaic converters. Background Technology

[0002] With the integration of numerous power electronic devices and nonlinear loads into power distribution networks, power quality pollution sources are becoming increasingly widespread and decentralized, leading to increasingly severe voltage and current harmonic distortion problems across the entire network. Most existing harmonic mitigation solutions rely on high-precision monitoring devices to collect real-time harmonic voltage and current phasors at each node, and then employ control algorithms to adjust the output current of each participating converter based on global information.

[0003] However, the above-mentioned scheme has the following limitations: First, relying on real-time acquisition of harmonic voltage and current phase will amplify the phase error of the fundamental voltage, affecting the control accuracy; Second, for multi-node systems, the real-time output changes of distributed photovoltaics will affect the converter's capacity, and load fluctuations will make it difficult to adapt the virtual conductance obtained by centralized optimization in real time; Third, existing schemes are prone to problems such as current exceeding limits, low node harmonic voltage, and underutilization of remaining capacity in real-time control, which limits their engineering practicality.

[0004] The information disclosed in this background section is intended only to enhance the understanding of the overall background of the present invention and should not be construed as an admission or in any way implying that the information constitutes prior art known to those skilled in the art. Summary of the Invention

[0005] The technical problem to be solved by the present invention is to provide a method and system for distributed harmonic regulation of distribution networks based on photovoltaic converters, which makes full use of the remaining capacity of photovoltaic converters and optimizes the coordinated control between multiple devices offline.

[0006] To achieve the above objectives, the technical solution adopted by this invention is: a distributed harmonic regulation method for distribution networks based on photovoltaic converters, comprising the following steps: Acquire and preprocess historical operating data of each node in the distribution network, and analyze and construct typical operating scenarios. The output voltage and output current of each photovoltaic converter are measured, and each harmonic current is extracted from the output current. The harmonic power and remaining capacity of each photovoltaic converter are calculated, and the harmonic compensation control architecture based on virtual harmonic conductance is determined. Based on the line parameters, power flow constraints and photovoltaic inverter constraints are determined, and a multi-objective optimization model is constructed with the objectives of minimizing global harmonic distortion rate and minimizing network active power loss. The multi-objective optimization model is solved according to different typical operating scenarios, an offline control table is formulated, the harmonic compensation output of each photovoltaic converter in each scenario is determined, and the compensation command of each photovoltaic converter is adjusted online according to the actual governance effect.

[0007] Furthermore, normalization is applied to the historical operating data to perform the preprocessing operation, and cluster analysis is used to construct the typical operating scenario conditions.

[0008] Furthermore, a cross-cancellation feedback method based on a second-order generalized integral orthogonal signal generator is used to separate and extract each harmonic current from the output current; The transfer function expression of the second-order generalized integral orthogonal signal generator is as follows: ; In the formula, ω h k is the resonant frequency. h This represents the bandwidth adjustment factor for h SOGI-QSG, used to determine the bandwidth of SOGI-QSG; and The transfer function for extracting the quadrature components of the h-th harmonic is given by ω. h The amplitude gain at each point is 1, and the phases are 0° and -90°, respectively. After cross-cancellation feedback, the harmonic currents are extracted from the output current using the following formula: ; ; in, and Let ω represent the equivalent extraction transfer functions of the h-th harmonic in-phase component and quadrature component obtained after cross-cancellation feedback. h The amplitude gain at that point is 1, and the phase difference is 90°.

[0009] Furthermore, the harmonic compensation control of the virtual harmonic conductance is achieved by changing the equivalent output impedance of the photovoltaic converter by setting the virtual harmonic conductance value, including the following steps: The voltage loop transfer function G is constructed using a quasi-PR controller. V (s); The delay element is equivalently treated using a second-order Pade approximation to obtain the current loop transfer function G. I (s); Based on the voltage loop transfer function G V (s) and the current loop transfer function G I (s) obtains the transmission voltage u of the distributed power inverter, which includes a virtual impedance control loop. o (s), the expression is: ; In the formula, G(s) is the voltage transfer function, and Z... eq (s) is the equivalent impedance of the inverter, Z o (s) and Z v (s) represent the equivalent impedance of the distributed power inverter itself and the additional virtual impedance, respectively, u o (s) represents the output voltage of the photovoltaic converter; This is the output voltage reference command; This provides the output current for the photovoltaic converter. The closed-loop transfer function from the voltage reference to the output voltage; This is the equivalent output impedance of the inverter. This is the inverter's equivalent output impedance without any added virtual impedance. The additional equivalent impedance introduced for the virtual impedance control circuit; Transfer function for voltage loop controller; Transfer function for current loop controller; This is the equivalent transfer function of the virtual impedance control element; For filtering inductors; For filtering capacitors; is the equivalent series resistance of the filter inductor or the equivalent resistance of the filter branch; s is the Laplace operator.

[0010] Furthermore, the determination of power flow constraints and photovoltaic inverter constraints based on line parameters includes fundamental power flow constraints, harmonic power flow constraints, virtual conductance stability constraints, photovoltaic converter compensation capacity constraints, and photovoltaic inverter operating condition constraints.

[0011] Furthermore, the construction of a multi-objective optimization model with the objectives of minimizing global harmonic distortion rate and minimizing network active power loss includes the following steps: Based on the objective of minimizing network active power loss, a network active power loss objective function is constructed. ; Based on the objective of minimizing harmonic distortion rate, a global harmonic distortion objective function is constructed. ; The objective function is subjected to a linear weighting method. and Combining these elements yields a single objective function f; Combining the single-objective function, power flow constraints, and photovoltaic inverter constraints, the multi-objective optimization model is obtained, and its expression is: ; In the formula, ω loss ω h Let ω be the weight coefficients corresponding to the objective function. loss+ω h =1, the larger the value, the higher the priority of the corresponding objective function term; Let the objective function be the network active power loss. The objective function is global harmonic distortion. and They are respectively and The normalized baseline value.

[0012] Furthermore, the online adjustment of compensation commands for each photovoltaic converter based on the actual governance effect includes: Based on the actual measured harmonic mitigation effect, conductance compensation commands are calculated in real time through a distributed controller; The harmonic compensation output in the offline control table is dynamically adjusted to ensure that the output current of each photovoltaic converter does not exceed its rated capacity.

[0013] Furthermore, the dynamic adjustment also includes: reusing remaining capacity to mitigate harmonics, thereby reducing the voltage distortion rate of the photovoltaic converter.

[0014] The present invention also provides a distributed harmonic regulation system for distribution networks based on photovoltaic converters, comprising: The scenario construction module is used to acquire and preprocess historical operating data of each node in the distribution network, and analyze and construct representative operating scenarios. The harmonic extraction module is used to measure the output voltage and output current of each photovoltaic converter, separate and extract each harmonic current from the output current, calculate the harmonic power and remaining capacity of each photovoltaic converter, and determine the harmonic compensation control architecture based on virtual harmonic conductance. The model building module is used to determine power flow constraints and photovoltaic inverter constraints based on line parameters, and to build a multi-objective optimization model with the objectives of minimizing global harmonic distortion rate and minimizing network active power loss. The online control module is used to solve the multi-objective optimization model according to different operating conditions, formulate offline control tables, determine the harmonic compensation output of each photovoltaic converter in each scenario, and adjust the compensation command of each photovoltaic converter online according to the actual treatment effect.

[0015] Furthermore, the power data at the load and PV are collected in real time by the PV power information acquisition device to obtain the historical operating data of each node.

[0016] The beneficial effects of this invention are as follows: By using offline table generation and online optimization of distributed harmonic mitigation in the distribution network, this invention can fully utilize the remaining capacity of photovoltaic converters while ensuring the safe operation of converters. It can also optimize the coordinated control between multiple devices offline, calculate conductance compensation commands in real time through a distributed controller, control the power output of the corresponding photovoltaic converters, construct an offline control table, and make fine adjustments to the online capacity based on this table, thereby improving the power quality of the distribution network. Attached Figure Description

[0017] 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 recorded in the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a flowchart illustrating the distributed harmonic regulation method for distribution networks based on photovoltaic converters in an embodiment of the present invention. Figure 2 This is a schematic diagram of the low-voltage system in an embodiment of the present invention; Figure 3 This is a schematic diagram of the transformer substation voltage curves under different scenarios in the embodiments of the present invention; Figure 4 As described in the embodiments of the present invention and A diagram showing the comparison of frequency characteristics; Figure 5 In the embodiments of the present invention, inverters G(s) and Z... o (s) Bode plot; Figure 6 This is a schematic diagram illustrating the changes in offline capacity utilization of each PV inverter in an embodiment of the present invention; Figure 7 This is a schematic diagram of the harmonic voltage distortion rate of the system bus in the pre-treatment stage of this embodiment of the invention; Figure 8 This is a schematic diagram of the harmonic voltage distortion rate of the system bus during the offline tabulation optimization stage in an embodiment of the present invention. Figure 9 This is a schematic diagram of the harmonic voltage distortion rate of the system bus after online optimization in an embodiment of the present invention. Detailed Implementation

[0019] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0020] It should be noted that when an element is referred to as being "fixed to" another element, it can be directly attached to the other element or there may be an intervening element. When an element is referred to as being "connected to" another element, it can be directly connected to the other element or there may be an intervening element. The terms "vertical," "horizontal," "left," "right," and similar expressions used herein are for illustrative purposes only and do not represent the only possible implementation.

[0021] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. The terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0022] like Figures 1 to 9 The distributed harmonic regulation method for distribution networks based on photovoltaic converters, as shown, includes the following steps: Acquire and preprocess historical operating data of each node in the distribution network, and analyze and construct typical operating scenarios. The output voltage and output current of each photovoltaic converter are measured, the harmonic currents are extracted from the output current, the harmonic power and remaining capacity of each photovoltaic converter are calculated, and the harmonic compensation control architecture based on virtual harmonic conductance is determined. Based on the line parameters, power flow constraints and photovoltaic inverter constraints are determined, and a multi-objective optimization model is constructed with the objectives of minimizing global harmonic distortion rate and minimizing network active power loss. The multi-objective optimization model is solved according to different typical operating scenarios, an offline control table is formulated, the harmonic compensation output of each photovoltaic converter in each scenario is determined, and the compensation command of each photovoltaic converter is adjusted online according to the actual treatment effect.

[0023] This invention utilizes offline tabulation and online optimization of distributed harmonic mitigation in the power distribution network. It can fully utilize the remaining capacity of photovoltaic converters while ensuring the safe operation of converters. It optimizes the coordinated control between multiple devices offline, calculates conductance compensation commands in real time through a distributed controller, controls the power output of the corresponding photovoltaic converters, and constructs an offline control table. Based on this table, online capacity fine-tuning is performed, thereby improving the power quality of the power distribution network.

[0024] Based on the above embodiments, normalization is used to preprocess historical operating data, and cluster analysis is used to construct typical operating scenarios.

[0025] The reference signals for the grid-connected inverter section of a photovoltaic system include the active power reference P. refReactive power reference Q ref and output harmonic current reference I href These reference values ​​can be generated and distributed to distributed photovoltaic systems in the distribution network by the dispatch or control center at regular intervals. During this period, the dispatch or control center needs to collect distribution network operation data, such as load power data provided by smart meters, and then establish an optimal power flow model for the distribution network to calculate the optimal combination of output reference values ​​for each photovoltaic system, thereby completing the basic control of the photovoltaic inverter.

[0026] Before implementing harmonic mitigation, corresponding harmonic control schemes need to be developed for different photovoltaic inverters, and high-precision voltage and current sensors that meet the mitigation requirements need to be configured. The specific modification method should be determined based on the required harmonic mitigation effect, choosing between "local harmonic current compensation" and "virtual harmonic conductance." To clarify the configuration schemes for different inverters in the distribution network, comprehensive harmonic mitigation simulations should be conducted based on historical distribution network operation data, and the scheme with the best average mitigation effect should be selected. Considering the large scale of historical operation data throughout the year, to reduce computational complexity, the power system operation status should first be clustered to extract representative typical operation scenarios, and then targeted mitigation should be implemented based on these typical scenarios. Before clustering, the historical operation status data for the past year needs to be normalized or standardized. Relevant variables include node power, photovoltaic output, harmonic voltages, harmonic currents and harmonic impedances injected by harmonic sources, and system background harmonics. Each sample point can be considered as a power quality mitigation operation scenario. Then, a typical scenario for comprehensive harmonic mitigation is constructed using the distance-based K-means clustering algorithm. The objective function is to minimize the sum of squared distances d from the samples within a cluster to the centroid. WCS :

[0027] In the formula, K represents the number of clusters; For the sample; Let K be the centroid of the m-th cluster. Clustering is performed with different K values, and the Calinski-Harabasz index is used to select the optimal K value, ensuring a small K value while maintaining high similarity within clusters and low similarity between clusters, ultimately yielding a typical operating scenario for the distribution network. Figure 2 Taking a real system in Zhejiang as an example, cluster analysis was performed based on historical data, dividing it into 7 typical scenarios. The voltage curves corresponding to different scenarios are shown below. Figure 3 As shown.

[0028] Based on the above embodiments, the implementation method of virtual harmonic conductance control is basically the same as that of virtual impedance control under the fundamental frequency, but it is still necessary to consider the output current i. oDifferent harmonic currents are extracted from the output current. This invention uses a cross-cancellation feedback method based on a second-order generalized integrators quadrature signal generator (SOGI-QSG) to separate and extract each harmonic current from the output current. The transfer function expression for a second-order generalized integral orthogonal signal generator is: ; In the formula, ω h k is the resonant frequency. h This represents the bandwidth adjustment factor for h SOGI-QSG, used to determine the bandwidth of SOGI-QSG; and The transfer function for extracting the quadrature components of the h-th harmonic is given by ω. h The amplitude gain at each point is 1, and the phases are 0° and -90°, respectively. After cross-cancellation feedback, the harmonic currents are extracted from the output current using the following formula: ; ; in, and Let ω represent the equivalent extraction transfer functions of the h-th harmonic in-phase component and quadrature component obtained after cross-cancellation feedback. h The amplitude gain at that point is 1, and the phase difference is 90°.

[0029] Separation and extraction of transfer functions for 3rd to 9th harmonics and Frequency characteristics for example Figure 4 As shown. It can be seen that, , In addition to ω h The gain at other resonant frequencies is almost zero, which means that it can reduce the mutual interference between the fundamental current and different harmonic currents during the harmonic current extraction process, and improve the accuracy of current extraction and subsequent virtual harmonic impedance control.

[0030] Based on the above embodiments, harmonic compensation control of virtual harmonic conductance is achieved by changing the equivalent output impedance of the photovoltaic converter by setting the virtual harmonic conductance value, including the following steps: The voltage loop transfer function G is constructed using a quasi-PR controller. V (s); The delay element is equivalently treated using a second-order Pade approximation to obtain the current loop transfer function G. I (s); Based on voltage loop transfer function G V (s) and current loop transfer function G I (s) obtains the transmission voltage u of the distributed power inverter, which includes a virtual impedance control loop. o (s), the expression is: ; In the formula, G(s) is the voltage transfer function, and Z... eq (s) is the equivalent impedance of the inverter, Z o (s) and Z v (s) represent the equivalent impedance of the distributed power inverter itself and the additional virtual impedance, respectively, u o (s) represents the output voltage of the photovoltaic converter; This is the output voltage reference command; This provides the output current for the photovoltaic converter. The closed-loop transfer function from the voltage reference to the output voltage; This is the equivalent output impedance of the inverter. This is the inverter's equivalent output impedance without any added virtual impedance. The additional equivalent impedance introduced for the virtual impedance control circuit; Transfer function for voltage loop controller; Transfer function for current loop controller; This is the equivalent transfer function of the virtual impedance control element; For filtering inductors; For filtering capacitors; is the equivalent series resistance of the filter inductor or the equivalent resistance of the filter branch; s is the Laplace operator.

[0031] Based on the above embodiments, considering the characteristics of power system fundamental and harmonic power flow, safe operation of photovoltaic inverters, and harmonic virtual conductance control, power flow constraints and photovoltaic inverter constraints are determined according to line parameters, including fundamental power flow constraints, harmonic power flow constraints, virtual conductance stability constraints, photovoltaic converter compensation capacity constraints, and photovoltaic inverter operating condition constraints, wherein: The fundamental wave power flow constraint is: ; ; In the formula, , and These are connected to node i respectively. Harmony The residential load between phases, the fundamental current of photovoltaic power, and the fundamental current of energy storage. , and The active power of residential load ARL, photovoltaic PVG and energy storage ESS, , and The reactive power of residential load ARL, PVG, and ESS energy storage. Let be the phase fundamental voltage phasor of node i; Let be the phase fundamental voltage phasor of node j; Inject current phasors into the phase fundamental wave at node i; For node i in the nodal admittance matrix at the fundamental frequency The mutual admittance element between the phase and the phase of node j.

[0032] Harmonic power flow constraints are: ; ; In the formula, and For connection at node i Harmony The h-th harmonic current generated by the residential load ARL between phases and the h-th harmonic current actively output by the energy storage ESS, where IHDh is the distortion rate of the h-th harmonic current. Phase angle of phasors; Let h be the phase parameter of the h-th harmonic in the load harmonic spectrum; Let h be the phase harmonic current phasor of node i; This represents the total number of nodes in the system. For the mutual admittance elements of the h-th harmonic between the phase of node i and the phase of node j in the nodal admittance matrix at the fundamental frequency; Let h be the phase harmonic voltage phasor of node j; The fundamental voltage vector injected between the two phases.

[0033] The voltage transfer function G(s) and its equivalent conductance Z of the inverter o (s) such as Figure 5 As shown, at the resonant frequency of the quasi-PR controller, the equivalent conductance Z of the distributed power inverter is... o The amplitude of (s) is close to 0, which means that its equivalent impedance at the fundamental and harmonic frequencies will be mainly determined by the virtual conductance. For ease of control and analysis, the virtual harmonic conductance values ​​at each harmonic frequency are set to be consistent. When the virtual conductance is adjusted individually, the total harmonic impedance from the distributed power inverter to its grid connection point has a stable variation range of only 3mH. When the h-th harmonic voltage at a certain node is less than the minimum allowable value u of the virtual conductance control... lowAt this time, the photovoltaic inverter at this node does not use virtual conductance control for the h-th harmonic, and if virtual conductance control is used for the h-th harmonic, the controlled node h-th harmonic voltage should be greater than or equal to u. low The virtual conductance stability constraint can be set as follows: ; In the formula, The amplitude of the h-th harmonic voltage or the distortion of the h-th harmonic voltage at node i; The lower threshold for voltage distortion to initiate harmonic compensation; The virtual harmonic conductance is set for the photovoltaic converter at node i for the h-th harmonic.

[0034] According to the IEEE Standard 1459-2010 standard for measuring power components related to power quality in power systems, the h-th harmonic power... and the total harmonic power of the inverter The compensation capacity constraint for the photovoltaic converter can be set as follows: ; ; In the formula, U 1，rms，i and I h，rms，i These represent the effective values ​​of the fundamental voltage and harmonic current of the photovoltaic inverter, respectively. The equivalent apparent power required to compensate the h-th harmonic for the photovoltaic converter at node i; The apparent power for total harmonic compensation undertaken by the photovoltaic converter at node i; Let be the effective value of the fundamental voltage at the photovoltaic converter port of node i; Let be the effective value of the h-th harmonic compensation current output by the photovoltaic converter at node i.

[0035] To ensure fairness in the governance process for photovoltaic converters, the capacity utilization rate of each converter follows the formula: .

[0036] The effective current of a photovoltaic (PV) converter during operation must not exceed the maximum limit of its inverter, and the harmonic power should not exceed its remaining capacity. Therefore, to avoid affecting the normal operation of the PV system, the inverter must not be overloaded. This necessitates limiting its output power and current. The operating conditions of the PV converter are as follows: ; ; In the formula, This indicates the rated capacity of the PV inverter. This indicates the rated current of the PV inverter. For node i Phase h harmonic voltage phasor For node i Phase h harmonic voltage phasor Let h be the h-th current vector output between the two phases of the PV inverter.

[0037] Based on the above embodiments, harmonic mitigation in distribution network systems considering power quality improvement is essentially an optimal power flow (OPF) problem. The key lies in establishing and solving the OPF model. Therefore, a multi-objective optimization model is constructed with the objectives of minimizing global harmonic distortion rate and minimizing network active power loss, including the following steps: Based on the objective of minimizing network active power loss, a network active power loss objective function is constructed. From the perspective of optimizing the operation of the distribution network, the goal is to minimize the active power loss of the network. The objective function expression for this project is: ; In the formula, N l Where H is the total number of lines, and H is the maximum harmonic order considered. For line k The active power loss under the h-th harmonic can be obtained by calculating the power difference between the two ends of the line, as shown in the following formula: ; In the formula, For line k Harmony The admittance at the h-th harmonic frequency between phases. `real` is the operator for taking the real part of a complex number. This is the conjugate operator. Based on the above two equations, the objective function f... loss It is a quadratic function of the node voltage, and because f loss Since ≥0, it is still a convex quadratic function of the node voltage variable.

[0038] When nonlinear loads exist in the distribution network, from the perspective of harmonic mitigation, the overall harmonic voltage distortion rate of the network should be minimized. Based on the objective of minimizing the harmonic distortion rate, a global harmonic distortion objective function is constructed. The expression is: ; In the formula, N n This represents the total number of nodes.

[0039] When considering multiple optimization objectives simultaneously, a linear weighted method can be used to optimize the objective function. and Combining these elements yields a single-objective function f; its expression is: ; Combining the single-objective function, power flow constraints, and photovoltaic inverter constraints, a multi-objective optimization model is obtained, expressed as: ; In the formula, ω loss ω h Let ω be the weight coefficients corresponding to the objective function. loss +ω h =1, the larger the value, the higher the priority of the corresponding objective function term; Let the objective function be the network active power loss. The objective function is global harmonic distortion. and They are respectively and The normalized baseline value; the constraints of the multi-objective optimization model are set as described in the above embodiments.

[0040] In the OPF model shown in the formula, it is noted that the constraints of the optimization problem that minimizes f consist entirely of first-order constraints, second-order constraints, and bilinear constraints. The overall problem is a non-convex quadratic programming problem. Using MATLAB's built-in solver, the non-convex quadratic programming problem is transformed into a convex model problem. Combining branch and bound and heuristic algorithms, after preprocessing and simplifying the model, the optimal solution is finally found. Then, the obtained harmonic virtual conductance Gi,h or harmonic current compensation coefficient ki,h is used as a control command and sent to each photovoltaic inverter participating in harmonic mitigation via one-way communication.

[0041] Based on the above embodiments, the compensation commands of each photovoltaic converter are adjusted online according to the actual governance effect, including: Based on the actual measured harmonic mitigation effect, conductance compensation commands are calculated in real time through a distributed controller; The harmonic compensation output in the offline control table is dynamically adjusted to ensure that the output current of each photovoltaic converter does not exceed its rated capacity.

[0042] by Figure 2 Taking the proposed practical system as an example, corresponding PV optimization control solutions are performed under seven different scenarios. This allows for the determination of the harmonic conductance and harmonic power corresponding to the initial PV converter. Since the system load varies irregularly in practice, fine-tuning is necessary based on the actual situation. Using the global governance effect as a boundary, the harmonic power absorbed by each PV inverter is dynamically adjusted according to the harmonic voltage distortion rate, thereby effectively improving the system's power quality. Taking the seven scenarios as examples, the load and PV parameters are shown in Table 1. Global optimization models are constructed for each scenario, and the control results are presented in an offline table as shown in Table 2. The online capacity fine-tuning is entirely based on the remaining PV capacity.

[0043] Table 1 Basic Information of Distribution Network Case Study

[0044] Table 2 Offline PV Control Table

[0045] Based on the above embodiments, dynamic adjustment also includes: reusing remaining capacity to manage harmonics, so as to reduce the voltage distortion rate of the photovoltaic converter.

[0046] Specifically, based on actual system scenario six, in order to better reflect the actual load changes and verify the effectiveness of the proposed "offline tabulation + online optimization" scheme, the load parameters in Table 1 were modified as shown in Table 3.

[0047] Table 3 Actual Test Parameters

[0048] Figure 6 To illustrate the time-varying offline capacity utilization of PV converters, after applying the proposed optimization algorithm, each PV converter fully absorbs the system's harmonic currents, achieving a utilization rate of 90%. However, due to... Figures 7 to 9 The harmonic voltage distortion rate of the system bus under different conditions shows that the system harmonic voltage distortion rate was 9.43% before the treatment. Harmonic treatment was performed on each PV unit according to the control parameters in Table 2, achieving a good treatment effect of 4.93%. The PV converters fully utilized their harmonic treatment potential. However, the voltage distortion rate did not meet the treatment requirements at this point, so online capacity fine-tuning was performed, utilizing 20% ​​of the remaining capacity for harmonic treatment again. At this point, the voltage distortion rate was significantly reduced to 3.82%. Experimental results show that the proposed control strategy has a good effect on harmonic voltage treatment of the transformer in the distribution area, while ensuring that the output current of the PV converter does not exceed the limit. The remaining capacity of the PV converter can be further utilized to achieve better compensation.

[0049] The present invention also provides a distributed harmonic regulation system for distribution networks based on photovoltaic converters, comprising: The scenario construction module is used to acquire and preprocess historical operating data of each node in the power distribution network, and analyze and construct typical operating scenario conditions. The harmonic extraction module is used to measure the output voltage and output current of each photovoltaic converter, separate and extract each harmonic current from the output current, calculate the harmonic power and remaining capacity of each photovoltaic converter, and determine the harmonic compensation control architecture based on virtual harmonic conductance. The model building module is used to determine power flow constraints and photovoltaic inverter constraints based on line parameters, and to build a multi-objective optimization model with the objectives of minimizing global harmonic distortion rate and minimizing network active power loss. The online control module is used to solve the multi-objective optimization model according to different typical operating scenarios, formulate offline control tables, determine the harmonic compensation output of each photovoltaic converter in each scenario, and adjust the compensation command of each photovoltaic converter online according to the actual governance effect.

[0050] The system in this invention constructs representative operating scenarios through cluster analysis, compressing massive amounts of historical operating data throughout the year into a finite number of typical scenarios, significantly reducing the computational complexity of offline optimization. Through virtual harmonic conductance control, it utilizes the remaining capacity of photovoltaic converters for harmonic compensation, achieving harmonic mitigation without the installation of additional equipment, thus reducing retrofit costs. An online fine-tuning mechanism enables each photovoltaic converter to dynamically adjust its compensation commands based on the actual mitigation effect, fully utilizing remaining capacity while ensuring the converters are not overloaded, thereby improving the system's robustness and adaptability. A multi-objective optimization model is constructed, simultaneously minimizing network losses and harmonic distortion rates, improving power quality while enhancing the economic efficiency of distribution network operation, ultimately improving the power quality of the distribution network.

[0051] Based on the above embodiments, a PV power information acquisition device collects power data from the load and PV in real time to obtain historical operating data for each node, facilitating subsequent voltage compensation control. Other modules can be deployed using components such as a central controller, transmitting the collected PV data to the PVs participating in the compensation task in real time. The remaining PVs then allocate compensation tasks based on this information. An offline control table is generated based on the collected information, and the online compensation capacity is fine-tuned based on the compensated voltage distortion rate.

[0052] Those skilled in the art should understand that this invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to this invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the invention as claimed. The scope of protection of this invention is defined by the appended claims and their equivalents.

Claims

1. A method for distributed harmonic regulation in distribution networks based on photovoltaic converters, characterized in that, Includes the following steps: Acquire and preprocess historical operating data of each node in the distribution network, and analyze and construct typical operating scenarios. The output voltage and output current of each photovoltaic converter are measured, and each harmonic current is extracted from the output current. The harmonic power and remaining capacity of each photovoltaic converter are calculated, and the harmonic compensation control architecture based on virtual harmonic conductance is determined. Based on the line parameters, power flow constraints and photovoltaic inverter constraints are determined, and a multi-objective optimization model is constructed with the objectives of minimizing global harmonic distortion rate and minimizing network active power loss. The multi-objective optimization model is solved according to different typical operating scenarios, an offline control table is formulated, the harmonic compensation output of each photovoltaic converter in each scenario is determined, and the compensation command of each photovoltaic converter is adjusted online according to the actual governance effect.

2. The distributed harmonic regulation method for distribution networks based on photovoltaic converters according to claim 1, characterized in that, The historical operating data is preprocessed using normalization, and the typical operating scenario conditions are constructed using cluster analysis.

3. The distributed harmonic regulation method for distribution networks based on photovoltaic converters according to claim 1, characterized in that, The method of cross-cancellation feedback based on a second-order generalized integral quadrature signal generator is used to separate and extract each harmonic current from the output current; The transfer function expression of the second-order generalized integral orthogonal signal generator is as follows: ； In the formula, ω h k is the resonant frequency. h This represents the bandwidth adjustment factor for h SOGI-QSG, used to determine the bandwidth of SOGI-QSG; and The transfer function for extracting the quadrature components of the h-th harmonic is given by ω. h The amplitude gain at each point is 1, and the phases are 0° and -90°, respectively. After cross-cancellation feedback, the harmonic currents are extracted from the output current using the following formula: ； ； in, and Let ω represent the equivalent extraction transfer functions of the h-th harmonic in-phase component and quadrature component obtained after cross-cancellation feedback. h The amplitude gain at that point is 1, and the phase difference is 90°.

4. The distributed harmonic regulation method for distribution networks based on photovoltaic converters according to claim 3, characterized in that, The harmonic compensation control of the virtual harmonic conductance is achieved by setting the virtual harmonic conductance value to change the equivalent output impedance of the photovoltaic converter, including the following steps: The voltage loop transfer function G is constructed using a quasi-PR controller. V (s); The delay element is equivalently treated using a second-order Pade approximation to obtain the current loop transfer function G. I (s); Based on the voltage loop transfer function G V (s) and the current loop transfer function G I (s) obtains the transmission voltage u of the distributed power inverter, which includes a virtual impedance control loop. o (s), the expression is: ； In the formula, G(s) is the voltage transfer function, and Z... eq (s) is the equivalent impedance of the inverter, Z o (s) and Z v (s) represent the equivalent impedance of the distributed power inverter itself and the additional virtual impedance, respectively, u o (s) represents the output voltage of the photovoltaic converter; This is the output voltage reference command; This provides the output current for the photovoltaic converter. The closed-loop transfer function from the voltage reference to the output voltage; This is the equivalent output impedance of the inverter. This is the inverter's equivalent output impedance without any added virtual impedance. The additional equivalent impedance introduced for the virtual impedance control circuit; Transfer function for voltage loop controller; Transfer function for current loop controller; This is the equivalent transfer function of the virtual impedance control element; For filtering inductors; For filtering capacitors; is the equivalent series resistance of the filter inductor or the equivalent resistance of the filter branch; s is the Laplace operator.

5. The distributed harmonic regulation method for distribution networks based on photovoltaic converters according to claim 1, characterized in that, The determination of power flow constraints and photovoltaic inverter constraints based on line parameters includes fundamental power flow constraints, harmonic power flow constraints, virtual conductance stability constraints, photovoltaic converter compensation capacity constraints, and photovoltaic inverter operating condition constraints.

6. The distributed harmonic regulation method for distribution networks based on photovoltaic converters according to claim 5, characterized in that, The construction of a multi-objective optimization model with the objectives of minimizing global harmonic distortion rate and minimizing network active power loss includes the following steps: Based on the objective of minimizing network active power loss, a network active power loss objective function is constructed. ; Based on the objective of minimizing harmonic distortion rate, a global harmonic distortion objective function is constructed. ; The objective function is subjected to a linear weighting method. and Combining these elements yields a single-objective function f; Combining the single-objective function, power flow constraints, and photovoltaic inverter constraints, the multi-objective optimization model is obtained, and its expression is: ； In the formula, ω loss ω h Let ω be the weight coefficients corresponding to the objective function. loss +ω h =1, the larger the value, the higher the priority of the corresponding objective function term; Let the objective function be the network active power loss. The objective function is global harmonic distortion. and They are respectively and The normalized baseline value.

7. The distributed harmonic regulation method for distribution networks based on photovoltaic converters according to claim 1, characterized in that, The online adjustment of compensation commands for each photovoltaic converter based on the actual governance effect includes: Based on the actual measured harmonic mitigation effect, conductance compensation commands are calculated in real time through a distributed controller; The harmonic compensation output in the offline control table is dynamically adjusted to ensure that the output current of each photovoltaic converter does not exceed its rated capacity.

8. The distributed harmonic regulation method for distribution networks based on photovoltaic converters according to claim 7, characterized in that, The dynamic adjustment also includes: reusing the remaining capacity to manage harmonics, so as to reduce the voltage distortion rate of the photovoltaic converter.

9. A distributed harmonic regulation system for distribution networks based on photovoltaic converters, characterized in that, include: The scenario construction module is used to acquire and preprocess historical operating data of each node in the power distribution network, and analyze and construct typical operating scenario conditions. The harmonic extraction module is used to measure the output voltage and output current of each photovoltaic converter, separate and extract each harmonic current from the output current, calculate the harmonic power and remaining capacity of each photovoltaic converter, and determine the harmonic compensation control architecture based on virtual harmonic conductance. The model building module is used to determine power flow constraints and photovoltaic inverter constraints based on line parameters, and to build a multi-objective optimization model with the goals of minimizing global harmonic distortion rate and minimizing network active power loss. The online control module is used to solve the multi-objective optimization model according to different typical operating scenarios, formulate offline control tables, determine the harmonic compensation output of each photovoltaic converter in each scenario, and adjust the compensation command of each photovoltaic converter online according to the actual governance effect.

10. The distributed harmonic regulation system for distribution networks based on photovoltaic converters according to claim 9, characterized in that, The power data of the load and PV are collected in real time by the PV power information acquisition device to obtain the historical operating data of each node.

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