Voltage regulation method and device of photovoltaic inverter, storage medium and electronic equipment

Abstract

This application discloses a voltage regulation method, apparatus, storage medium, and electronic device for a photovoltaic inverter. The method includes: acquiring the historical reactive power and desired voltage level of a target photovoltaic inverter in a target area, the load current corresponding to multiple harmonics of the load in the current cycle, and the voltage corresponding to multiple harmonics of the grid connection point in the current cycle; determining the energy command and harmonic commands corresponding to multiple harmonics of the target photovoltaic inverter based on the historical reactive power and desired voltage level; and determining and regulating the target voltage regulation command of the target photovoltaic inverter in the current cycle based on the load current, voltage, energy command, harmonic commands, and desired voltage level corresponding to multiple harmonics. This application solves the technical problem in related technologies where inaccurate determination of the photovoltaic inverter's voltage regulation command leads to unsatisfactory voltage regulation performance.

Description

Technical Field

[0001] This application relates to the field of power systems, and more specifically, to a voltage regulation method, apparatus, storage medium, and electronic equipment for a photovoltaic inverter. Background Technology

[0002] With the large-scale integration of distributed photovoltaic (PV) systems into distribution networks, residential PV inverters, as coupling nodes between distributed power sources and loads, have seen their intermittent and nonlinear output characteristics significantly impact power quality in the distribution area. This is particularly true in scenarios with high load harmonic content, easily leading to prominent issues such as point-of-compatibility (PCC) voltage distortion, excessive harmonics, and voltage fluctuations. Therefore, accurately and efficiently determining the voltage regulation commands of PV inverters and achieving proactive harmonic current injection compensation has become a key technical aspect for ensuring the safe and stable operation of distribution networks and improving the capacity for renewable energy absorption.

[0003] In related technologies, droop control and reinforcement learning models are used to determine the voltage regulation command of a photovoltaic inverter. The droop control method adjusts the reactive / active output of the photovoltaic inverter by detecting the voltage amplitude or frequency deviation of the power consumption circuit (PCC), but it can only achieve coarse voltage support and cannot provide targeted compensation for specific harmonics. The reinforcement learning model learns regulation strategies from historical data, but it lacks a verifiable and auditable incentive and constraint mechanism, leading to unreliable voltage regulation commands. Therefore, related technologies suffer from the technical problem of inaccurate voltage regulation command determination, resulting in unsatisfactory voltage regulation performance of the photovoltaic inverter.

[0004] There is currently no effective solution to the above problems. Summary of the Invention

[0005] This application provides a voltage regulation method, apparatus, storage medium, and electronic device for a photovoltaic inverter, to at least solve the technical problem in the related art where the voltage regulation effect of the photovoltaic inverter is not ideal due to inaccurate determination of the voltage regulation command.

[0006] According to one aspect of the embodiments of this application, a voltage regulation method for a photovoltaic inverter is provided, comprising: acquiring the historical reactive power and willingness level of a target photovoltaic inverter in a target area, the load current corresponding to multiple harmonics of the load in the target area in the current cycle, and the voltage corresponding to multiple harmonics of the grid connection point of the target area in the current cycle, wherein the willingness level is used to characterize the degree to which the user corresponding to the target photovoltaic inverter is willing to respond to the voltage regulation command; and determining the energy command and harmonic commands corresponding to multiple harmonics of the target photovoltaic inverter in the current cycle based on the historical reactive power and willingness level, wherein the energy command is used to indicate the upper limit of the total electrical energy that the target photovoltaic inverter can consume in the current cycle, and the harmonic commands are... This is used to indicate the upper limit of the harmonic current amplitude of the corresponding subharmonic that can be injected into the target photovoltaic inverter in the current cycle; based on the load current, voltage, energy command, harmonic command, and willingness level corresponding to each harmonic, the initial virtual admittance of the target photovoltaic inverter for each harmonic in the current cycle is determined; based on the initial virtual admittance of each harmonic, the target virtual admittance of the target photovoltaic inverter for each harmonic in the current cycle is determined; based on the target virtual admittance of each harmonic, the target voltage regulation command of the target photovoltaic inverter for the current cycle is determined, and the output voltage of the target photovoltaic inverter is regulated using the target voltage regulation command.

[0007] According to another aspect of the embodiments of this application, a voltage regulation device for a photovoltaic inverter is provided, comprising: a data acquisition module, configured to acquire the historical reactive power and willingness level of a target photovoltaic inverter in a target area, the load current corresponding to multiple harmonics of the load in the target area in the current cycle, and the voltage corresponding to multiple harmonics of the grid connection point of the target area in the current cycle, wherein the willingness level is used to characterize the degree to which the user corresponding to the target photovoltaic inverter is willing to respond to the voltage regulation command; and a first determination module, configured to determine the energy command and harmonic command corresponding to multiple harmonics of the target photovoltaic inverter in the current cycle based on the historical reactive power and willingness level, wherein the energy command is used to indicate the upper limit of the total electrical energy that the target photovoltaic inverter can consume in the current cycle, and the harmonic command is used to indicate the upper limit of the total electrical energy that the target photovoltaic inverter can consume in the current cycle. The system comprises four modules: a first module, a second module, and a third module. The first module determines the upper limit of the harmonic current amplitude of the target photovoltaic inverter for the corresponding harmonic in the current cycle; a second module determines the initial virtual admittance of the target photovoltaic inverter for the corresponding harmonic in the current cycle based on the load current, voltage, energy command, harmonic command, and willingness level corresponding to each harmonic; a third module determines the target virtual admittance of the target photovoltaic inverter for the corresponding harmonic in the current cycle based on the initial virtual admittance; and a fourth module determines the target voltage regulation command of the target photovoltaic inverter for the current cycle based on the target virtual admittance, and regulates the output voltage of the target photovoltaic inverter using the target voltage regulation command.

[0008] According to another aspect of the embodiments of this application, a non-volatile storage medium is provided, which stores a plurality of instructions adapted for a voltage regulation method for a photovoltaic inverter, any one of which is loaded by a processor.

[0009] According to another aspect of the embodiments of this application, an electronic device is provided, including: one or more processors and a memory, the memory being used to store one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors cause the one or more processors to implement any one of the voltage regulation methods for a photovoltaic inverter.

[0010] According to another aspect of the embodiments of this application, a computer program product is provided, which, when executed on a data processing device, is a program adapted to perform the steps of a voltage regulation method for a photovoltaic inverter.

[0011] In this embodiment, the historical reactive power and willingness level of the target photovoltaic inverter in the target area are obtained, along with the load current corresponding to multiple harmonics of the load in the target area during the current cycle, and the voltage corresponding to multiple harmonics of the grid connection point of the target area during the current cycle. The willingness level characterizes the degree to which the user corresponding to the target photovoltaic inverter is willing to respond to voltage regulation commands. Based on the historical reactive power and willingness level, the energy command and harmonic commands corresponding to multiple harmonics of the target photovoltaic inverter in the current cycle are determined. The energy command indicates the upper limit of the total electrical energy that the target photovoltaic inverter can consume in the current cycle, and the harmonic commands indicate the upper limit of the total electrical energy that the target photovoltaic inverter can consume during the current cycle. The upper limit of the harmonic current amplitude that can be injected for the corresponding subharmonic in the current cycle is determined. Based on the load current, voltage, energy command, harmonic command, and willingness level corresponding to each harmonic, the initial virtual admittance of the target photovoltaic inverter for each harmonic in the current cycle is determined. Based on the initial virtual admittance corresponding to each harmonic, the target virtual admittance of the target photovoltaic inverter for each harmonic in the current cycle is determined. Based on the target virtual admittance corresponding to each harmonic, the target voltage regulation command of the target photovoltaic inverter for the current cycle is determined, and the output voltage of the target photovoltaic inverter is regulated using the target voltage regulation command. This method aims to determine the energy command and harmonic command of the target photovoltaic inverter by acquiring the historical reactive power and desired level of the target photovoltaic inverter in the target area, the load current corresponding to the multiple harmonics of the load in the target area, and the voltage corresponding to the multiple harmonics of the grid connection point in the target area. This, in turn, determines the target voltage regulation command of the target photovoltaic inverter, thereby improving the accuracy of the target voltage regulation command determination and thus enhancing the voltage regulation quality of the target photovoltaic inverter. This also solves the technical problem in related technologies where inaccurate determination of the photovoltaic inverter's voltage regulation command leads to unsatisfactory voltage regulation performance. Attached Figure Description

[0012] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings:

[0013] Figure 1 This is a flowchart of a voltage regulation method for a photovoltaic inverter according to an embodiment of this application;

[0014] Figure 2 This is a structural block diagram of an optional distributed photovoltaic collaborative control system provided according to an embodiment of this application;

[0015] Figure 3This is a schematic diagram of a voltage regulation device for a photovoltaic inverter according to an embodiment of this application;

[0016] Figure 4 This is a structural diagram of an electronic device provided according to an embodiment of this application. Detailed Implementation

[0017] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0018] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0019] It should be noted that the information collected in this application (including but not limited to historical reactive power, willingness level, preset short-term basic score, preset medium-term basic score, preset long-term basic score, confidence coefficient, incentive coefficient, comprehensive contribution factor, and total regulation benefit, etc.) and data (including but not limited to load current corresponding to multiple harmonics, voltage corresponding to multiple harmonics, voltage deviation, event flags, and equipment life indicators, etc.) are information and data authorized by the user or fully authorized by all parties. Furthermore, the collection, storage, use, processing, transmission, provision, disclosure, and application of related data all comply with relevant laws, regulations, and standards, necessary confidentiality measures have been taken, and they do not violate public order and good morals. Corresponding operation entry points are provided for users to choose to authorize or refuse. For example, interfaces are set up between this system and relevant users or institutions, providing users with corresponding operation entry points for users to choose to agree to or refuse automated decision results; if the user chooses to refuse, the process proceeds to the expert decision-making process.

[0020] According to an embodiment of this application, a method embodiment for voltage regulation of a photovoltaic inverter is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0021] Figure 1 This is a flowchart of a voltage regulation method for a photovoltaic inverter according to an embodiment of this application, such as... Figure 1 As shown, the method includes the following steps:

[0022] Step S102: Obtain the historical reactive power and willingness level of the target photovoltaic inverter in the target area, the load current corresponding to the multiple harmonics of the load in the target area in the current cycle, and the voltage corresponding to the multiple harmonics of the grid connection point of the target area in the current cycle. The willingness level is used to characterize the degree to which the user corresponding to the target photovoltaic inverter is willing to respond to the voltage regulation command.

[0023] This involves acquiring the historical reactive power and willingness level of the target photovoltaic (PV) inverters in the target distribution area, the load current corresponding to multiple harmonics of the load in the target distribution area during the current cycle, and the voltage corresponding to multiple harmonics of the grid connection point of the target distribution area during the current cycle. The target distribution area includes multiple PV inverters, and the willingness level characterizes the degree to which the user corresponding to the target PV inverter is willing to respond to voltage regulation commands. Through this data, personalized modeling and multi-dimensional constraint coordination of the target PV inverter's regulation capability can be achieved, improving the accuracy, predictability, and user participation matching of the target voltage regulation command determination results, providing a highly reliable and adaptable input foundation for distributed collaborative control.

[0024] Optionally, the willingness level selected by the user through the APP or Web interface can be mapped to a virtual admittance feasible domain, incentive coefficient, and margin commitment mechanism. Table 1 shows the mapping relationship of user willingness levels. When a user selects a willingness level of L2 or above, a margin must be locked on-chain. If subsequent sampling fails, the smart contract will automatically deduct the margin and downgrade the level. At the same time, the willingness level directly affects the subsequent weight adjustment of contribution factors, the virtual admittance feasible domain of frequency domain optimization, and the settlement incentive coefficient.

[0025] Table 1. Mapping Relationship of User Willingness Level

[0026]

[0027] Step S104: Based on historical reactive power and willingness level, determine the energy command and harmonic commands corresponding to multiple harmonics of the target photovoltaic inverter in the current cycle. The energy command is used to indicate the upper limit of the total electrical energy that the target photovoltaic inverter can consume in the current cycle, and the harmonic command is used to indicate the upper limit of the harmonic current amplitude of the corresponding harmonic that the target photovoltaic inverter can inject in the current cycle.

[0028] It is understandable that personalized energy commands (i.e., energy budgets) and multiple harmonic commands (i.e., harmonic budgets corresponding to multiple harmonics) are dynamically generated based on historical reactive power and user willingness levels. This enables precise constraints and differentiated control of the target photovoltaic inverter in terms of both total power consumption and harmonic compensation capability, effectively balancing power quality management efficiency and equipment lifespan, and improving the reliability and executability of system collaborative control.

[0029] In one optional embodiment, based on historical reactive power and willingness level, the energy command and harmonic commands corresponding to multiple harmonics of the target photovoltaic inverter in the current cycle are determined, including: determining the short-term contribution factor of the target photovoltaic inverter based on the first reactive power of the first historical cycle in the historical reactive power; determining the medium-term contribution factor of the target photovoltaic inverter based on the second reactive power of the second historical cycle in the historical reactive power, wherein the time length corresponding to the first historical cycle is shorter than the time length corresponding to the second historical cycle; determining the long-term contribution factor of the target photovoltaic inverter based on the third reactive power of the third historical cycle in the historical reactive power, wherein the time length corresponding to the second historical cycle is shorter than the time length corresponding to the third historical cycle; determining the comprehensive contribution factor of the target photovoltaic inverter in the current cycle based on the short-term contribution factor, medium-term contribution factor, long-term contribution factor, and willingness level; determining the energy command based on the comprehensive contribution factor and the total energy command of the target distribution area in the current cycle; and determining the harmonic commands corresponding to multiple harmonics based on the comprehensive contribution factor and the total harmonic commands corresponding to multiple harmonics of the target distribution area in the current cycle.

[0030] It is understood that the energy command and the harmonic commands corresponding to multiple harmonics are determined in the following manner. First, based on the first reactive power of the first historical period (e.g., 10 seconds), the second reactive power of the second historical period (e.g., 5–15 minutes), and the third reactive power of the third historical period (e.g., 1 hour), the short-term, medium-term, and long-term contribution factors of the target photovoltaic inverter are determined respectively. The time length corresponding to the first historical period is shorter than that corresponding to the second historical period, and the time length corresponding to the second historical period is shorter than that corresponding to the third historical period. Second, based on the aforementioned short-term, medium-term, and long-term contribution factors, combined with the willingness level, the comprehensive contribution factor of the target photovoltaic inverter in the current period is determined. This comprehensive contribution factor is used to quantitatively characterize the global adjustment priority of the target photovoltaic inverter in integrating historical response capabilities, user willingness levels, and the health status of the photovoltaic inverter equipment across multiple time scales, achieving a differentiated and weighted comprehensive evaluation of the contribution value of the participating entity (i.e., the photovoltaic inverter). Finally, based on the comprehensive contribution factor and the total energy command of the target distribution area in the current cycle, the energy command is determined. Similarly, based on the comprehensive contribution factor and the total harmonic command corresponding to each harmonic in the target distribution area in the current cycle, the harmonic commands corresponding to each harmonic are determined. By integrating historical response capabilities across multiple time scales, user willingness levels, and equipment health status to construct a dynamic comprehensive contribution factor, and adaptively allocating energy and harmonic commands accordingly, distributed photovoltaic inverters achieve precise and coordinated control that balances equipment lifespan constraints and user incentive mechanisms while ensuring power quality management effectiveness. This enhances the overall system response reliability, fairness, and long-term operational stability.

[0031] Optionally, the short-term contribution factor is used to quantify the target photovoltaic inverter's immediate reactive power compensation response capability to PCC harmonic voltage surges within a second-level timescale (e.g., a 10-second window), reflecting its dynamic support performance during power quality emergencies. The medium-term contribution factor is used to quantify the stability and durability of the target photovoltaic inverter's continuous reactive power output regulation within a minute-level timescale (e.g., a 5–15-minute window), assessing its collaborative regulation resilience under moderate and sustained voltage fluctuations. The long-term contribution factor is used to quantify the target photovoltaic inverter's comprehensive carrying capacity of cumulative energy contribution and equipment lifespan loss within an hour-level timescale (e.g., a 1-hour window), reflecting its safe adjustment budget margin during long-term operation.

[0032] Optionally, short-term contribution factors Characterizing the target photovoltaic inverter i Emergency response capabilities on a second-level timescale are achieved through an exponential smoothing algorithm, based on the most recent... The historical reactive power response within the time window (i.e., the first historical period, such as 10 seconds) is calculated, highlighting the recent dynamic contribution. The following methods can be used to determine this:

[0033]

[0034] in, For time window The window normalization constant, For a moment t Historical reactive power For the current moment, It is the first smoothing constant.

[0035] Optionally, the medium-term contribution factor Reflecting the target photovoltaic inverter i Sustained conditioning endurance on a minute-scale timescale, based on The historical reactive power response within the time window (i.e., the second historical period, such as 5–15 minutes) is calculated to measure the stable output capability of the target photovoltaic inverter. The following methods can be used to determine this:

[0036]

[0037] in, For time window The window normalization constant, This is the second smoothing constant.

[0038] Optionally, long-term contribution factor Evaluation of target photovoltaic inverter i The comprehensive energy contribution and equipment lifespan loss margin on hourly and longer timescales can be based on The historical reactive power response within the time window (i.e., the third historical period, such as 1 hour) is calculated, or the remaining carrying capacity is dynamically assessed based on the equipment health model. The following methods can be used to determine this:

[0039]

[0040] in, For time window The window normalization constant, It is the third smoothing constant.

[0041] In one optional embodiment, the comprehensive contribution factor of the target photovoltaic inverter for the current period is determined based on short-term contribution factor, medium-term contribution factor, long-term contribution factor, and willingness level. This includes: obtaining the voltage deviation of the grid-connected point for the current period, the event flag of the target distribution area for the current period, the equipment life index of the target photovoltaic inverter for the current period, and the preset short-term basic score, preset medium-term basic score, and preset long-term basic score of the target photovoltaic inverter. The event flag is used to indicate whether the target distribution area is in a disturbed state in the current period, and the equipment life index is used to quantify the aging degree of the target photovoltaic inverter in the current period. Based on the voltage deviation, event flag, and preset short-term basic score, the initial short-term contribution score of the target photovoltaic inverter is determined; and the willingness level is used... The initial short-term contribution score is corrected to obtain the target short-term contribution score of the target photovoltaic inverter. Based on the equipment life index and the preset medium-term baseline score, the target medium-term contribution score of the target photovoltaic inverter is determined. The preset long-term baseline score is determined as the target long-term contribution score of the target photovoltaic inverter. Based on the target short-term contribution score, target medium-term contribution score, and target long-term contribution score, the short-term weight of the short-term contribution factor of the target photovoltaic inverter in the current period, the medium-term weight of the medium-term contribution factor of the target photovoltaic inverter in the current period, and the long-term weight of the long-term contribution factor of the target photovoltaic inverter in the current period are determined. Based on the short-term contribution factor, medium-term contribution factor, long-term contribution factor, short-term weight, medium-term weight, and long-term weight, the comprehensive contribution factor is determined.

[0042] The comprehensive contribution factor of the target photovoltaic inverter for the current cycle is determined as follows: First, the voltage deviation of the grid connection point of the target distribution area in the current cycle, the event indicators of the target distribution area in the current cycle (e.g., voltage surge, harmonic surge), the equipment life index of the target photovoltaic inverter in the current cycle, and the preset short-term, preset medium-term, and preset long-term base scores of the target photovoltaic inverter are obtained. Second, based on the voltage deviation, event indicators, and preset short-term base scores, the initial short-term contribution score of the target photovoltaic inverter is calculated, and the initial short-term contribution score is corrected using a willingness level to obtain the target short-term contribution score of the target photovoltaic inverter. Then, based on the equipment life index and the preset medium-term base score, the target medium-term contribution score of the target photovoltaic inverter is calculated. Finally, the preset long-term base score is determined as the target long-term contribution score of the target photovoltaic inverter. Then, based on the target short-term contribution score, target medium-term contribution score, and target long-term contribution score, each contribution score is normalized to obtain the short-term weight of the target photovoltaic inverter's short-term contribution factor, the medium-term weight of the target photovoltaic inverter's medium-term contribution factor, and the long-term weight of the target photovoltaic inverter's long-term contribution factor in the current period. Finally, the short-term contribution factor, medium-term contribution factor, long-term contribution factor, short-term weight, medium-term weight, and long-term weight are weighted and summed, and the summation result is normalized to obtain the comprehensive contribution factor of the target photovoltaic inverter in the current period. By integrating voltage deviation, event flags, equipment life indicators, and user willingness levels, the contribution scores of multiple time scales are dynamically calculated and weighted to achieve adaptive, differentiated, and interpretable evaluation of the comprehensive contribution factor, improving the fairness, robustness, and consistency of user incentives in the allocation of energy and harmonic resources in distributed photovoltaic collaborative control.

[0043] Optionally, the willingness level is introduced to modify only the initial short-term contribution score, which is a differentiated design based on the high initiative and controllability of user response behavior in a short time scale. In scenarios requiring sub-second response times (such as voltage spikes or harmonic surges), the system needs to quickly mobilize the adjustment capabilities of users with high willingness levels to achieve emergency management. At this time, the user's subjective willingness to participate (such as L3 / L4 level) directly determines whether they can and are willing to exert maximum effort. Therefore, by weighting and amplifying the initial short-term contribution score through willingness level, it can effectively incentivize users with high willingness levels to play a "peak response" role and improve the dynamic stability of the system. The medium-term contribution factor mainly reflects the continuous adjustment endurance of photovoltaic inverter equipment within a few minutes. Its essence is dominated by physical characteristics (such as temperature rise and thermal inertia) and life loss model. The willingness level has been constrained in the equipment access stage through the previous deposit lock-in and authorization mechanism, and there is no need to repeatedly weight it in the calculation, otherwise it will lead to redundancy in the incentive mechanism. The long-term contribution factor focuses on the energy accumulation and health status of the equipment throughout its entire life cycle. It is essentially an objective reflection of the equipment's "capacity stock" and has no direct causal relationship with the user's subjective willingness. If it is forcibly modified, it may distort the fairness and security of resource allocation. Therefore, introducing intention level correction only in short-term scores achieves the goal of "incentivizing high intention levels to participate in emergency response" while avoiding the increased system complexity and evaluation distortion caused by multiple layers of repeated corrections, ensuring the optimal balance of the comprehensive contribution factor in the three dimensions of dynamics, stability, and interpretability.

[0044] Optionally, directly using a preset long-term baseline score as the target long-term contribution score for the photovoltaic inverter is a design based on the inherent stability and predictability of the photovoltaic inverter's health status and energy contribution capability over a long timescale. The long-term contribution reflects the "energy reserve" or "carrying capacity margin" that the photovoltaic inverter can continuously and safely contribute during hourly or even daily operation, based on its rated capacity, aging characteristics, and lifespan model. This value is pre-determined by the equipment's factory parameters, historical cumulative operating losses, and a preset lifespan decay curve. It has the characteristics of being relatively constant within a period and having a non-sudden response. Its core function is to ensure the safety and sustainability of the system's long-term operation, rather than a dynamic response to transient disturbances. Attempting to dynamically correct it by introducing short-term fluctuations such as real-time voltage deviations or event flags would instead introduce noise interference, undermining the fairness of resource allocation and the reliability of equipment protection mechanisms. Therefore, setting the long-term contribution score as a preset baseline value ensures its stability as a "capability limit" and forms a hierarchical constraint with the medium-term contribution factor (dynamically adjusted by equipment life indicators). This approach safeguards the equipment safety boundary while providing incentive response, achieving a systematic trade-off between "flexible short-term incentives and rigid long-term constraints," and improving the engineering feasibility and long-term operational robustness of the control strategy.

[0045] Optionally, the voltage deviation at the grid connection point in the current cycle can be used as a reference. Event markers for the target area in the current cycle (Such as voltage surges, harmonic spikes), current cycle target photovoltaic inverter equipment life indicators and target photovoltaic inverter i Corresponding user willingness level Calculate the target photovoltaic inverter for the current cycle. i The short-term weights of short-term contributing factors The medium-term weight of the medium-term contribution factor and the long-term weights of long-term contribution factors. .

[0046]

[0047]

[0048]

[0049]

[0050]

[0051]

[0052]

[0053] in, For the initial short-term contribution score, To contribute points to the target in the short term. To contribute points to the target in the mid-term To contribute points to the goal in the long term. To preset a short-term baseline score, To preset the mid-term baseline score, To preset a long-term baseline score, The weighting coefficient for voltage deviation controls the strength of its influence on the short-term contribution score. The incentive coefficient for the event marker controls the amplification effect of "event triggering" on the short-term contribution score. The incentive gain coefficient controls the amplification effect of user willingness level on short-term contribution scores. The penalty coefficient for lifetime loss controls the intensity of the suppression of lifetime loss on the mid-term contribution score.

[0054] Optionally, the target photovoltaic inverter for the current cycle i Comprehensive contribution factor The following methods can be used to determine this:

[0055]

[0056] in, This refers to the number of photovoltaic inverters included in the target distribution area. , and These are the current period, the target area, and the [number]th [unit]. j The short-term, medium-term, and long-term contribution factors of each photovoltaic inverter. For the current cycle, the first in the target transformer area j Short-term weights of the short-term contribution factors of each photovoltaic inverter For the current cycle, the first in the target transformer area j The medium-term weight of the medium-term contribution factor of each photovoltaic inverter. For the current cycle, the first in the target transformer area j The long-term weight of the long-term contribution factor of each photovoltaic inverter.

[0057] Optionally, the energy budget of the target photovoltaic inverter i in the current period. The following methods can be used to determine this:

[0058]

[0059] in, The total energy command for the target distribution area in the current cycle.

[0060] Optionally, in the current cycle, the target photovoltaic inverter i The harmonic budgets for the multiple harmonics are as follows: ,in, This represents a set of multiple harmonics. h Harmonic budget for subharmonics The following methods can be used to determine this:

[0061]

[0062] in, For the target area in the current cycle h Total harmonic command for subharmonics. For the first h The importance coefficient of subharmonics.

[0063] Step S106: Based on the load current, voltage, energy command, harmonic command, and willingness level corresponding to each harmonic, determine the initial virtual admittance of the target photovoltaic inverter for each harmonic in the current cycle.

[0064] It is understandable that, based on the load current, voltage, harmonic command, energy command, and willingness level corresponding to multiple harmonics, the initial virtual admittance of the target photovoltaic inverter in each harmonic frequency band is dynamically calculated. This achieves distributed, adaptive, and coordinated control that balances the safety operation boundary of the photovoltaic inverter equipment and the willingness of users to participate, while meeting the total energy budget and harmonic compensation targets. This improves the harmonic suppression efficiency of the target distribution area and the fairness, controllability, and robustness of resource allocation.

[0065] In one optional embodiment, based on the load current corresponding to each harmonic, the voltage corresponding to each harmonic, the energy command, the harmonic command corresponding to each harmonic, and the willingness level, the initial virtual admittance of the target photovoltaic inverter corresponding to each harmonic in the current cycle is determined, including: constructing a target optimization function based on the voltage and load current corresponding to each harmonic, wherein the target optimization function is used to minimize the sum of the squares of the total harmonic current at the grid connection point and the virtual admittance adjustment cost of the target photovoltaic inverter; constructing a first constraint condition based on the energy command, wherein the first constraint condition is used to ensure that the active power consumption of the target photovoltaic inverter does not exceed the energy command; and based on the load current corresponding to each harmonic, the initial virtual admittance of the target photovoltaic inverter corresponding to each harmonic in the current cycle is determined, including: constructing a target optimization function based on the voltage and load current corresponding to each harmonic, wherein the target optimization function is used to minimize the sum of the squares of the total harmonic current at the grid connection point and the virtual admittance adjustment cost of the target photovoltaic inverter; constructing a first constraint condition based on the energy command, wherein the first constraint condition is used to ensure that the active power consumption of the target photovoltaic inverter does not exceed the energy command; and constructing a target optimization function based on the load current, voltage, energy command, harmonic command, and willingness level, based on the load current, voltage, energy command, harmonic command, and willingness level, based on the load current, voltage, energy command, and the load current corresponding to each harmonic ... Based on the harmonic command, second constraints are constructed for each harmonic, whereby the second constraints ensure that the amplitude of the initial virtual admittance of the target photovoltaic inverter under the corresponding harmonic does not exceed the virtual admittance threshold determined based on the harmonic command for the corresponding harmonic. Based on the intention level, third constraints are constructed for each harmonic, whereby the third constraints ensure that the initial virtual admittance of the target photovoltaic inverter under the corresponding harmonic does not exceed the feasible region of virtual admittance under the corresponding harmonic determined based on the intention level. Based on the objective optimization function, the first constraints, the second constraints for each harmonic, and the third constraints for each harmonic, the initial virtual admittance for each harmonic is determined.

[0066] It is understood that the initial virtual admittance of the target photovoltaic inverter for each harmonic in the current cycle is determined as follows: First, an objective optimization function is constructed based on the voltage and load current corresponding to each harmonic to minimize the sum of the squares of the total harmonic currents at the grid connection point and the virtual admittance adjustment cost of the target photovoltaic inverter. Second, based on the energy command, a first constraint condition is constructed to ensure that the active power consumption of the target photovoltaic inverter does not exceed the energy command. Next, based on the harmonic commands corresponding to each harmonic, a second constraint condition is constructed to ensure that the amplitude of the initial virtual admittance of the target photovoltaic inverter under the corresponding harmonic does not exceed the virtual admittance threshold determined based on the harmonic command for the corresponding harmonic. Then, based on the willingness level, a third constraint condition is constructed to ensure that the initial virtual admittance of the target photovoltaic inverter under the corresponding harmonic does not exceed the feasible region of the virtual admittance under the corresponding harmonic determined based on the willingness level. Finally, based on the aforementioned objective optimization function, the first constraint, the second constraint corresponding to each harmonic, and the third constraint corresponding to each harmonic, the initial virtual admittances for each harmonic are obtained. By constructing a multi-constraint optimization model that integrates energy budget, harmonic budget, and user willingness level within the feasible region, with harmonic suppression effectiveness and adjustment cost as objectives, distributed adaptive solutions for virtual admittances under each harmonic are achieved. This improves the accuracy of multi-harmonic frequency band collaborative suppression, the overall steady-state performance of the system, and the fairness and feasibility of resource allocation, while ensuring equipment safety and user rights.

[0067] Optionally, for the target photovoltaic inverter i , No. h Virtual admittance of subharmonics With the h Virtual impedance of subharmonics The relationship between them is: ,in, , For target photovoltaic inverters i The h The resistance of the subharmonics For target photovoltaic inverters i The h The reactance of the subharmonic, It is the imaginary unit.

[0068] Optionally, the objective function is:

[0069]

[0070]

[0071] in, The weighting coefficient for the h-th harmonic is... The total current of the h-th harmonic at the grid connection point. These are weighting coefficients used to control the trade-off between "compensation costs" and "compensation effects." Let be the virtual admittance cost coefficient of the target photovoltaic inverter i at the h-th harmonic. The voltage of the h-th harmonic at the grid connection point. Let be the load current of the h-th harmonic.

[0072] Optionally, the first constraint is:

[0073]

[0074] in, For the target photovoltaic inverter i under the h-th harmonic, due to the response The instantaneous active power loss generated.

[0075] Optionally, the second constraint conditions corresponding to each harmonic are as follows:

[0076]

[0077] in, Let i be the maximum allowable virtual admittance value of the target photovoltaic inverter i under the h-th harmonic. As an engineering safety factor, This is a normalization factor used to achieve magnitude constraints for the current budget within the current cycle.

[0078] Optionally, the third constraint conditions corresponding to each harmonic are as follows:

[0079]

[0080] in, For the desired level of the target photovoltaic inverter i The feasible region of virtual admittance under the h-th harmonic.

[0081] Based on the objective function, the first constraint, the second constraint corresponding to each harmonic, and the third constraint corresponding to each harmonic, determine the initial virtual admittance corresponding to each harmonic. .

[0082] Step S108: Based on the initial virtual admittance corresponding to each harmonic, determine the target virtual admittance of the target photovoltaic inverter for each harmonic in the current cycle.

[0083] It is understandable that, based on the initial virtual admittance corresponding to each harmonic, the target virtual admittance corresponding to each harmonic can be obtained through iterative optimization. This enables adaptive matching and safe and controllable allocation of the target photovoltaic inverter's collaborative compensation capability in multiple harmonic frequency bands, thereby improving the systematicness, real-time performance, and fairness of user participation in harmonic governance.

[0084] In one optional embodiment, determining the target virtual admittance of the target photovoltaic inverter for each harmonic in the current cycle, based on the initial virtual admittance corresponding to each harmonic, includes: determining reference virtual admittance corresponding to each harmonic based on the voltage and load current corresponding to each harmonic; iteratively updating the initial virtual admittance corresponding to each harmonic based on the reference virtual admittance and the initial dual variables corresponding to each harmonic to obtain the updated virtual admittance corresponding to each harmonic; and further updating the target virtual admittance based on the reference virtual admittance and the initial dual variables corresponding to each harmonic. The updated virtual admittance is obtained by iteratively updating the initial dual variables corresponding to each harmonic. Based on the reference virtual admittance and the updated dual variables corresponding to each harmonic, the updated virtual admittance corresponding to each harmonic is iteratively updated to obtain the updated virtual admittance corresponding to each harmonic. The updated virtual admittance corresponding to each harmonic is iteratively updated until the iteration stopping condition is met, thus obtaining the target virtual admittance corresponding to each harmonic.

[0085] The target virtual admittance of the target photovoltaic inverter for each harmonic in the current cycle is determined as follows: First, based on the voltage and load current corresponding to each harmonic, a reference virtual admittance is calculated for each harmonic, where the reference virtual admittance is the target value of the virtual admittance for the corresponding harmonic. Second, based on the reference virtual admittance and the initial dual variables corresponding to each harmonic, the initial virtual admittance is iteratively updated to obtain the updated virtual admittance for each harmonic. Then, based on the updated virtual admittance and the reference virtual admittance, the initial dual variables are iteratively updated to obtain the updated dual variables. Finally, based on the reference virtual admittance and the updated dual variables, the updated virtual admittance is iteratively updated to obtain the updated virtual admittance for each harmonic. The updated virtual admittances corresponding to multiple harmonics are iteratively updated using the same method described above until the iteration stops. The virtual admittances corresponding to the multiple harmonics obtained in the last iteration are then determined as the target virtual admittances for each harmonic. Through independent modeling of multiple harmonic frequency bands and distributed alternating iteration, collaborative convergence of the virtual admittances of the target photovoltaic inverter is achieved without global synchronization, accurately matching harmonic compensation requirements while strictly satisfying individual constraint and energy budget, thus improving the accuracy of the determined target virtual admittances for each harmonic.

[0086] Optionally, the above-mentioned iteration stopping conditions may include, but are not limited to, the change in virtual admittance obtained from two adjacent iterations being lower than a preset threshold, reaching the maximum number of iterations, or the residual of the dual variable converging to within the allowable error range.

[0087] Optionally, the even variable is the updated value of the Lagrange multiplier introduced by the target photovoltaic inverter in the previous iteration cycle to satisfy the PCC total harmonic admittance consistency. It is used to guide the target photovoltaic inverter to converge toward the globally optimal virtual admittance distribution in the current iteration cycle, under the premise of satisfying its own desire level constraint and energy budget.

[0088] Alternatively, the ADMM algorithm can be used to iterate K( (This is repeated twice, with the goal of) distributively solving for the target virtual admittance of the target photovoltaic inverter i in the current cycle for multiple harmonics. .

[0089] Optionally, the reference virtual admittance corresponding to each harmonic is calculated. And broadcast. Reference virtual admittance of the h-th harmonic. The following methods can be used to determine this:

[0090]

[0091] Optionally, the target photovoltaic inverter i locally updates the initial virtual admittance. The updated virtual admittance corresponding to each harmonic was obtained. The updated virtual admittance of the h-th harmonic of the target photovoltaic inverter i. The following methods can be used to determine this:

[0092]

[0093] in, Let be the initial dual variable of the h-th harmonic. The consistency penalty weight.

[0094] Optionally, update The updated dual variables corresponding to multiple harmonics are obtained. The updated dual variable of the h-th harmonic. The following methods can be used to determine this:

[0095]

[0096] Optionally, the virtual admittance and dual variables are updated iteratively in the manner described above, and updated in subsequent iterations. In and The virtual admittance is then updated iteratively until the iteration stopping condition is met, thus obtaining the target virtual admittance corresponding to each harmonic. ,Will This is converted into the target virtual impedance corresponding to each harmonic. And distribute it to the target photovoltaic inverter i.

[0097] Step S110: Based on the target virtual admittance corresponding to multiple harmonics, determine the target voltage regulation command of the target photovoltaic inverter in the current cycle, and use the target voltage regulation command to regulate the output voltage of the target photovoltaic inverter.

[0098] It is understandable that by generating precise target voltage regulation commands based on the target virtual admittance corresponding to multiple harmonics and then regulating them, harmonic pollution at the grid connection point can be effectively suppressed. At the same time, it ensures that the regulation behavior is strictly limited by user will and energy budget, significantly improving the real-time performance, controllability and reliability of system coordination in power quality management.

[0099] In one optional embodiment, determining the target voltage regulation command of the target photovoltaic inverter in the current cycle based on the target virtual admittance corresponding to each harmonic includes: obtaining the target virtual impedance corresponding to each harmonic of the target photovoltaic inverter in the current cycle based on the target virtual admittance corresponding to each harmonic; determining the voltage regulation amount corresponding to each harmonic of the target photovoltaic inverter in the current cycle based on the target virtual impedance corresponding to each harmonic and the harmonic current generated by the target photovoltaic inverter in response to the target virtual impedance corresponding to each harmonic; and determining the target voltage regulation command based on the voltage regulation amount corresponding to each harmonic and the basic voltage regulation amount of the target photovoltaic inverter in the current cycle.

[0100] It can be understood that, based on the target virtual admittance corresponding to each harmonic, the target virtual impedance of the target photovoltaic inverter in the current cycle is determined for each harmonic. Combined with the harmonic current corresponding to each harmonic, the voltage regulation amount corresponding to each harmonic of the target photovoltaic inverter in the current cycle is determined. Here, the harmonic current is the current generated by the target photovoltaic inverter in response to the target virtual impedance of the corresponding harmonic. Based on the voltage regulation amounts corresponding to each harmonic and the basic voltage regulation amount of the target photovoltaic inverter in the current cycle, the target voltage regulation command of the target photovoltaic inverter in the current cycle is determined. By inversely calculating the target virtual impedance based on the target virtual admittance, and combining the harmonic current to accurately calculate the voltage regulation amount corresponding to each harmonic, as well as the basic voltage regulation amount, the target voltage regulation command is accurately determined, ensuring that the inverter accurately outputs the desired power quality compensation waveform while meeting distributed optimization constraints.

[0101] Alternatively, SOGI (Second-Order Generalized Integrator) or RDF (Recursive Discrete Fourier Transform) can be used to extract the harmonic currents corresponding to multiple harmonics in real time. Calculate the voltage regulation corresponding to the multiple harmonics of the target photovoltaic inverter i in the current cycle. The voltage regulation of the h-th harmonic of the target photovoltaic inverter i. The following methods can be used to determine this:

[0102]

[0103] Optionally, the target voltage regulation command for the target photovoltaic inverter i in the current cycle is determined. . The following methods can be used to determine this:

[0104]

[0105] in, This represents the base voltage regulation of the target photovoltaic inverter i for the current cycle.

[0106] Optionally, if If the signal exceeds the allowable range of the desired level, the system will automatically truncate it to the boundary value defined by that desired level and record the abnormal event in the local log. Simultaneously, it will trigger a desired level assessment and early warning for the target PV inverter i. If the target voltage regulation command causes the harmonic current output by the target PV inverter to exceed its rated limit, the system will automatically scale the voltage regulation proportionally to ensure that the output harmonic current remains within the safe operating range, preventing equipment overload or protection activation. During communication interruptions, the system switches to the default virtual impedance. When the communication interruption between the target PV inverter and the edge aggregator lasts for more than a preset threshold, the system will automatically switch to the preset default virtual impedance parameters (such as low gain, conservative compensation mode) to maintain basic harmonic suppression capabilities and ensure local power quality management functions are maintained even without upper-level commands, until communication is restored and resynchronized.

[0107] In an optional embodiment, after regulating the output voltage of the target photovoltaic inverter using the target voltage regulation command, the method further includes: determining the regulation benefit of the target photovoltaic inverter in the current period due to its participation in voltage regulation based on the confidence coefficient, excitation coefficient, comprehensive contribution factor, and the total regulation benefit of the target distribution area in the current period, wherein the confidence coefficient is used to indicate whether the target photovoltaic inverter has successfully responded to the target voltage regulation command, and the excitation coefficient is determined based on the willingness level.

[0108] It is understandable that, based on confidence coefficient, incentive coefficient, comprehensive contribution factor and total regulation benefit of the target transformer area, the regulation benefit generated by the target photovoltaic inverter participating in voltage regulation in the current cycle is dynamically quantified. This achieves fair, reliable and automated incentive settlement based on verifiable response, user willingness as weight, and multi-scale contribution, thereby enhancing user participation and the sustainability of system collaborative governance.

[0109] Optionally, the incentive coefficient is determined based on the willingness level and is used to characterize the differentiated compensation intensity of the user corresponding to the target photovoltaic inverter in the process of participating in power quality governance, reflecting the depth of participation and willingness to transfer resources.

[0110] Optionally, the regulation benefits generated by the current cycle target photovoltaic inverter i due to its participation in voltage regulation. The following methods can be used to determine this:

[0111]

[0112] in, is the confidence coefficient for the target photovoltaic inverter i, used to indicate whether the target photovoltaic inverter successfully responded to the target voltage regulation command; it is 1 for success and 0 for failure. The total adjustment benefit of the target distribution area in the current cycle. For the target photovoltaic inverter i at the desired level The incentive coefficient below, For the photovoltaic inverters j in the target area, at the willingness level The incentive coefficient below, Let be the confidence coefficient of photovoltaic inverter j.

[0113] Through the above steps S102 to S110, the historical reactive power and desired level of the target photovoltaic inverter in the target area, the load current corresponding to the multiple harmonics of the load in the target area, and the voltage corresponding to the multiple harmonics of the grid connection point in the target area can be obtained to determine the energy command and harmonic command corresponding to the multiple harmonics of the target photovoltaic inverter, thereby determining the target voltage regulation command of the target photovoltaic inverter. This achieves the technical effect of improving the accuracy of the target voltage regulation command determination result of the target photovoltaic inverter, thereby improving the voltage regulation quality of the target photovoltaic inverter, and solving the technical problem in related technologies where the voltage regulation effect of the photovoltaic inverter is not ideal due to the inaccurate determination result of the voltage regulation command of the photovoltaic inverter.

[0114] Based on the above embodiments and optional embodiments, this application proposes an implementation method for an optional voltage regulation method of a photovoltaic inverter, which can be understood as a distributed photovoltaic collaborative control system. The distributed photovoltaic collaborative control method constructs a system and method integrating user willingness management, verifiable contribution measurement (including anti-cheating mechanisms), dynamic allocation of contribution factors across multiple time scales, and frequency domain collaborative control based on virtual harmonic impedance. This effectively addresses the core pain points of existing technologies, such as low user participation, single contribution measurement, reliance on global strong synchronization for harmonic compensation, and lack of reliable guarantees in the settlement mechanism. It achieves precise power quality management at the second to minute level, and reliable automated settlement at the hour / day level, taking into account both the lifespan loss of photovoltaic inverter equipment and user incentives, thereby improving user participation and the steady-state stability and dynamic response capability of the distribution network system.

[0115] Figure 2 This is a structural block diagram of an optional distributed photovoltaic collaborative control system provided according to an embodiment of this application, such as... Figure 2As shown, the distributed photovoltaic (PV) collaborative control system includes a data acquisition unit, a user intention unit, an edge aggregator, a multi-timescale scheduling unit, a frequency domain collaborative control and virtual harmonic impedance optimization unit, a blockchain / settlement unit, an anti-fraud and verification unit, and an operation management and reporting unit. The data acquisition unit is responsible for real-time acquisition of local operating data from the target PV inverter (e.g., historical reactive power), voltage / load current at the target area's grid connection point, event flags, and other multi-source inputs, providing basic data support for voltage regulation. The user intention unit, through a user-end APP (Application) or Web (World Wide Web) interface, allows users to independently select their participation intention level (L0–L4) and bind the corresponding adjustment permissions (including the virtual admittance feasible domains corresponding to multiple harmonics under the corresponding intention level), incentive coefficients, and margin commitment mechanisms, realizing the digital expression and dynamic management of user participation intention levels. The edge aggregator is deployed at the edge of the target area, undertaking local data aggregation, preliminary data verification, abnormal behavior identification, and initiation of challenge-response mechanisms. The multi-timescale scheduling unit, based on a three-tier architecture of planning, scheduling, and execution layers, dynamically generates the energy budget (i.e., energy command) for the target photovoltaic inverter and the harmonic budget (i.e., harmonic command) for each harmonic. The frequency domain collaborative control and virtual harmonic impedance optimization unit, at the execution layer, uses the ADMM (Alternating Direction Method of Multipliers) distributed algorithm to independently optimize the virtual admittance for each harmonic, generating the target virtual admittance for each harmonic and sending it to the inverter, achieving second-level harmonic collaborative suppression without global synchronization. The blockchain / settlement unit uses consortium blockchain or entrusted ledger technology to store key data such as contribution summaries, response signatures, and settlement vouchers on the blockchain. Through smart contracts, it automatically executes margin deductions, incentive allocations, and settlement payments, constructing an immutable, trustworthy, and transparent economic incentive closed loop. The anti-fraud and verification unit comprehensively utilizes technologies such as TPM (Trusted Platform Module) / PKI (Public Key Infrastructure) digital signatures, random sampling, neighborhood cross-validation, digital twin simulation verification, and TEE (Trusted Execution Environment) to perform multi-dimensional verification of the authenticity of photovoltaic inverter equipment responses, effectively preventing data tampering and fraudulent participation. The operations management and reporting unit provides settlement details queries, system audit trails, user behavior analysis, and visual dashboards, supporting efficient management, compliance auditing, and continuous optimization for operators.

[0116] The user willingness unit maps the level of willingness selected by the user through the APP or Web interface to a virtual admittance feasible domain, incentive coefficient, and margin commitment mechanism. Table 1 shows the mapping relationship of user willingness levels.

[0117] When a user selects an L2 or higher willingness level, a margin deposit must be locked on-chain. If a subsequent random check fails, the smart contract will automatically deduct the margin deposit and downgrade the user's willingness level. Furthermore, the willingness level directly affects the subsequent weighting of contribution factors, the feasible domain of virtual admittance for frequency domain optimization, and the settlement incentive coefficient.

[0118] The multi-timescale scheduling unit receives the user's desired level and outputs the energy budget and harmonic budget for the target photovoltaic inverter.

[0119] Short-term contribution factor Characterizing the target photovoltaic inverter i Emergency response capabilities on a second-level timescale are achieved through an exponential smoothing algorithm, based on the most recent... The historical reactive power response within the time window (i.e., the first historical period, such as 10 seconds) is calculated, highlighting the recent dynamic contribution. The following method is used to determine:

[0120]

[0121] in, For time window The window normalization constant, For a moment t Historical reactive power For the current moment, It is the first smoothing constant.

[0122] Mid-term contribution factor Reflecting the target photovoltaic inverter i Sustained conditioning endurance on a minute-scale timescale, based on The historical reactive power response within the time window (i.e., the second historical period, such as 5–15 minutes) is calculated to measure the stable output capability of the target photovoltaic inverter. The following method is used to determine:

[0123]

[0124] in, For time window The window normalization constant, This is the second smoothing constant.

[0125] Long-term contribution factor Evaluation of target photovoltaic inverter iThe comprehensive energy contribution and equipment lifespan loss margin on hourly and longer timescales can be based on The historical reactive power response within the time window (i.e., the third historical period, such as 1 hour) is calculated, or the remaining carrying capacity is dynamically assessed based on the equipment health model. The following method is used to determine:

[0126]

[0127] in, For time window The window normalization constant, It is the third smoothing constant.

[0128] Based on the voltage deviation of the grid connection point in the current cycle Event markers for the target area in the current cycle (Such as voltage surges, harmonic spikes), current cycle target photovoltaic inverter equipment life indicators and target photovoltaic inverter i Corresponding user willingness level Calculate the target photovoltaic inverter for the current cycle. i The short-term weights of short-term contributing factors The medium-term weight of the medium-term contribution factor and the long-term weights of long-term contribution factors. .

[0129]

[0130]

[0131]

[0132]

[0133]

[0134]

[0135]

[0136] in, For the initial short-term contribution score, To contribute points to the target in the short term. To contribute points to the target in the mid-term To contribute points to the goal in the long term. To preset a short-term baseline score, To preset the mid-term baseline score, To preset a long-term baseline score, The weighting coefficient for voltage deviation controls the strength of its influence on the short-term contribution score. The incentive coefficient for the event marker controls the amplification effect of "event triggering" on the short-term contribution score. The incentive gain coefficient controls the amplification effect of user willingness level on short-term contribution scores. The penalty coefficient for lifetime loss controls the intensity of the suppression of lifetime loss on the mid-term contribution score.

[0137] Current cycle target photovoltaic inverter i Comprehensive contribution factor The following method is used to determine:

[0138]

[0139] in, This refers to the number of photovoltaic inverters included in the target distribution area. , and These are the current period, the target area, and the [number]th [unit]. j The short-term, medium-term, and long-term contribution factors of each photovoltaic inverter. For the current cycle, the first in the target transformer area j Short-term weights of the short-term contribution factors of each photovoltaic inverter For the current cycle, the first in the target transformer area j The medium-term weight of the medium-term contribution factor of each photovoltaic inverter. For the current cycle, the first in the target transformer area j The long-term weight of the long-term contribution factor of each photovoltaic inverter.

[0140] Current cycle, energy budget of target photovoltaic inverter i The following method is used to determine:

[0141]

[0142] in, The total energy command for the target distribution area in the current cycle.

[0143] Current cycle, target photovoltaic inverter i The harmonic budgets for the multiple harmonics are as follows: ,in, This represents a set of multiple harmonics. h Harmonic budget for subharmonics The following method is used to determine:

[0144]

[0145] in, For the target area in the current cycle h Total harmonic command for subharmonics. For the first h The importance coefficient of subharmonics.

[0146] Frequency domain collaborative control and virtual harmonic impedance optimization unit receives target photovoltaic inverter i of , and By solving the target virtual impedance of each photovoltaic inverter device through distributed optimization, PCC harmonic collaborative suppression is achieved.

[0147] For the target photovoltaic inverter i , No. h Virtual admittance of subharmonics With the h Virtual impedance of subharmonics The relationship between them is: ,in, , For target photovoltaic inverters i The h The resistance of the subharmonics For target photovoltaic inverters i The h The reactance of the subharmonic, It is the imaginary unit.

[0148] The objective optimization function is:

[0149]

[0150]

[0151] in, The weighting coefficient for the h-th harmonic is... The total current of the h-th harmonic at the grid connection point. These are weighting coefficients used to control the trade-off between "compensation costs" and "compensation effects." Let be the virtual admittance cost coefficient of the target photovoltaic inverter i at the h-th harmonic. The voltage of the h-th harmonic at the grid connection point. Let be the load current of the h-th harmonic.

[0152] The first constraint is:

[0153]

[0154] in, For the target photovoltaic inverter i under the h-th harmonic, due to the response The instantaneous active power loss generated.

[0155] The second constraint conditions corresponding to each harmonic are:

[0156]

[0157] in, Let i be the maximum allowable virtual admittance value of the target photovoltaic inverter i under the h-th harmonic. As an engineering safety factor, This is a normalization factor used to achieve magnitude constraints for the current budget within the current cycle.

[0158] The third constraint conditions corresponding to each harmonic are:

[0159]

[0160] in, For the desired level of the target photovoltaic inverter i The feasible region of virtual admittance under the h-th harmonic.

[0161] Based on the objective function, the first constraint, the second constraint corresponding to each harmonic, and the third constraint corresponding to each harmonic, determine the initial virtual admittance corresponding to each harmonic. .

[0162] Using the ADMM algorithm, iterate K( (This is repeated twice, with the goal of) distributively solving for the target virtual admittance of the target photovoltaic inverter i in the current cycle for multiple harmonics. .

[0163] The aggregator calculates the reference virtual admittance corresponding to each harmonic. And broadcast. Reference virtual admittance of the h-th harmonic. The following method is used to determine:

[0164]

[0165] Target photovoltaic inverter i Local update of initial virtual admittance The updated virtual admittance corresponding to each harmonic was obtained. The updated virtual admittance of the h-th harmonic of the target photovoltaic inverter i. The following method is used to determine:

[0166]

[0167] in, Let be the initial dual variable of the h-th harmonic. The consistency penalty weight.

[0168] renew The updated dual variables corresponding to multiple harmonics are obtained. The updated dual variable of the h-th harmonic. The following method is used to determine:

[0169]

[0170] The virtual admittance and dual variables are updated iteratively in the manner described above, and then updated in subsequent iterations. In and The virtual admittance is then updated iteratively until the iteration stopping condition is met, thus obtaining the target virtual admittance corresponding to each harmonic. ,Will This is converted into the target virtual impedance corresponding to each harmonic. And distribute it to the target photovoltaic inverter i.

[0171] The harmonic currents corresponding to multiple harmonics are extracted in real time using SOGI (Second-Order Generalized Integrator) or RDF (Recursive Discrete Fourier Transform). .

[0172] Calculate the voltage regulation corresponding to the multiple harmonics of the target photovoltaic inverter i in the current cycle. The voltage regulation of the h-th harmonic of the target photovoltaic inverter i. The following method is used to determine:

[0173]

[0174] Determine the target voltage regulation command for target photovoltaic inverter i in the current cycle. . The following method is used to determine:

[0175]

[0176] in, This represents the base voltage regulation of the target photovoltaic inverter i for the current cycle.

[0177] like If the signal exceeds the allowable range of the desired level, the system will automatically truncate it to the boundary value defined by that desired level and record the abnormal event in the local log. Simultaneously, it will trigger a desired level assessment and early warning for the target PV inverter i. If the target voltage regulation command causes the harmonic current output by the target PV inverter to exceed its rated limit, the system will automatically scale the voltage regulation proportionally to ensure that the output harmonic current remains within the safe operating range, preventing equipment overload or protection activation. During communication interruptions, the system switches to the default virtual impedance. When the communication interruption between the target PV inverter and the edge aggregator lasts for more than a preset threshold, the system will automatically switch to the preset default virtual impedance parameters (such as low gain, conservative compensation mode) to maintain basic harmonic suppression capabilities and ensure local power quality management functions are maintained even without upper-level commands, until communication is restored and resynchronized.

[0178] The blockchain / settlement unit locks margin in smart contracts for users with L2 and higher willingness levels, with deductions and returns executed automatically. The edge aggregator... (e.g., 1 minute) Generate contribution package (timestamp, device ID (Identifier)). The data (original data hash, device private key signature) is stored on the blockchain in an immutable manner. The time window for contributing data to be packaged and uploaded to the blockchain.

[0179] The edge aggregator continuously records the deviation between the actual response value of each photovoltaic inverter device to the target voltage regulation command and the target voltage regulation command. To prevent data forgery and false reporting, the system periodically and randomly initiates a "challenge-response" verification: the aggregator issues a temporary command to a designated device (e.g., adjusting a certain harmonic virtual impedance to a specific value); after the device executes the command locally, it generates a response packet containing a timestamp, command ID, response value, and private key signature, and returns it to the aggregator; the aggregator uploads the challenge command hash and the device response hash together to the blockchain for evidence storage. If the device response deviation exceeds a preset threshold (e.g., ±10%), or fails to respond within the specified time, the smart contract automatically determines that the response has failed, triggering the margin deduction mechanism and automatically downgrading the user's willingness level (e.g., L3→L2).

[0180] The smart contract automatically settles the regulation benefits generated by the photovoltaic inverter i due to its participation in voltage regulation in the current cycle target period. . The following method is used to determine:

[0181]

[0182] in, is the confidence coefficient for the target photovoltaic inverter i, used to indicate whether the target photovoltaic inverter successfully responded to the target voltage regulation command; it is 1 for success and 0 for failure. The total adjustment benefit of the target distribution area in the current cycle. For the target photovoltaic inverter i at the desired level The incentive coefficient below, For the photovoltaic inverters j in the target area, at the willingness level The incentive coefficient below, Let be the confidence coefficient of photovoltaic inverter j.

[0183] To balance system efficiency, data privacy, and auditability, the blockchain / settlement unit adopts a lightweight, high-throughput consortium blockchain architecture. Specific optimization strategies are as follows: only contribution aggregation summaries (such as device IDs and normalized contribution factors) are processed. The system stores the cryptographic hash values ​​of the original data (including timestamps) on the blockchain, while the original operational data (such as voltage, current, and power sampling sequences) remains on local edge devices or aggregators, preventing sensitive data leakage and effectively reducing on-chain storage overhead and privacy risks. It adopts a consortium blockchain architecture and uses PBFT (Practical Byzantine Fault Tolerance) or Raft consensus algorithms to achieve fast consistency confirmation between nodes, offering advantages such as high throughput, low latency, and strong consistency. Transaction confirmation time is less than 1 second, fully meeting the collaborative needs of minute-level settlement and second-level control. Since nodes are institutionally controllable and do not require mining, the system does not rely on Proof of Work (PoW), and transaction fees are close to zero. This supports high-frequency, low-cost on-chain deployment of massive distributed photovoltaic inverter devices, enabling economically sustainable large-scale deployment. In scenarios with high security requirements, the system can be equipped with Zero-Knowledge Proof (ZKP) technology, which enables photovoltaic inverter equipment to prove the authenticity and compliance of its contribution value to the aggregator or smart contract without disclosing the original data, thus achieving the privacy protection goal of "verification without disclosure".

[0184] As the core support layer of the system's trust mechanism, the anti-cheating and verification unit effectively prevents malicious behaviors such as data forgery, instruction tampering, and false contributions through multi-layered and dynamic verification methods. Specifically, it includes the following three verification mechanisms:

[0185] Continuous signature verification and consistency detection: The edge aggregator performs multi-dimensional real-time verification on each contribution packet before it is uploaded to the chain, including: signature verification, time consistency verification, neighborhood consistency verification, and periodic random sampling. The selected photovoltaic inverter devices are required to send back the signature fragment of their original measurement data (including the original sampling sequence and its private key signature). The aggregator compares the hash with the on-chain evidence by locally recalculating the hash, so as to achieve "data traceability and behavior verification".

[0186] Dynamic verification of digital twins at the distribution station level: Construct a digital twin model that is fully synchronized with the physical distribution station, detect the deviation between the observed value and the simulated value, and when the deviation exceeds the preset tolerance threshold (such as ±15%) and continues to exceed the set period, automatically trigger the high-risk audit process, freeze the settlement qualification of the relevant equipment, and notify the operator to intervene in the verification, so as to realize the intelligent early warning capability of "simulation-driven anomaly detection".

[0187] End-to-end evidence chain storage and traceability auditing: All key operational events—including challenge command issuance, device response submission, sampling result determination, deposit deduction, settlement voucher generation, etc.—generate a unique hash digest and are stored on the blockchain, forming an immutable and complete evidence chain. Auditors can trace the entire lifecycle behavior of any device in chronological order through a blockchain explorer or authorized interface, achieving a transparent management mechanism of "traceable behavior, delineable responsibility, and adjudicable disputes."

[0188] Based on the distributed photovoltaic collaborative control system, an implementation example is proposed: distributed photovoltaic collaborative control and settlement at the substation level.

[0189] A certain distribution area has 50 residential photovoltaic inverters, and the 5th harmonic emission level at the PCC (Power Distribution Center) of the distribution area exceeds the standard. After system deployment:

[0190] User preference selection: Some users choose L2 (limited adjustment), while others choose L3 (high preference). The system sets the virtual admittance feasible region based on the preference level.

[0191] Multi-timescale contribution factors: Short-term / medium-term / long-term contribution factors for each photovoltaic inverter device are calculated every minute, and weights are dynamically adjusted based on voltage deviation to generate energy budget and harmonic budget. Devices with high willingness to invest receive higher comprehensive contribution factors and budgets.

[0192] Frequency domain optimization: The aggregator broadcasts the PCC voltage, load current and reference virtual admittance every 200ms. Each device iterates in parallel using ADMM to solve for the virtual admittance and finally issues the target virtual admittance command.

[0193] Blockchain on-chain: Contribution factors will be integrated every hour. Stored on the blockchain, smart contracts automatically settle and adjust benefits.

[0194] Challenge-Response: Randomly inspect 10% of the equipment and require them to adjust the virtual impedance to a specific value. If the response deviation exceeds the threshold, the deposit will be deducted and the equipment will be downgraded.

[0195] The results showed that the PCC 5th harmonic current suppression rate reached 75%, the equipment life loss was balanced, the user adjustment benefits and contribution were positively correlated, and the user participation rate increased to over 90%.

[0196] The above optional implementation methods achieve at least the following effects:

[0197] (1) The effectiveness of power quality management has been significantly improved. By introducing a distributed optimization mechanism for virtual harmonic impedance with multiple time scales, multiple distributed photovoltaic inverters can be effectively coordinated to achieve second-level emergency response and hour-level lifetime balance compensation without the need for global synchronization, thereby reducing the harmonic distortion rate at the grid connection point of the distribution network in the distribution area;

[0198] (2) User participation has been significantly enhanced. Based on a flexible adaptation mechanism with multi-level willingness levels (L0–L4), combined with differentiated incentive coefficients and on-chain margin constraints, users can choose the depth of participation according to the condition of their own photovoltaic inverter equipment;

[0199] (3) The credibility and automation level of the settlement mechanism have been greatly improved. Based on the immutable evidence storage and challenge-response dual verification mechanism of blockchain, the provability and auditability of contribution measurement are realized. Combined with the automatic execution of settlement and margin management by smart contracts, disputes caused by manual accounting and trust costs in intermediate links are completely eliminated. A closed-loop trust system of "measurable contribution, verifiable behavior and automatic incentive redemption" is constructed, which significantly reduces operation and maintenance costs and improves system operation efficiency and fairness.

[0200] It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases the steps shown or described may be executed in a different order than that shown here.

[0201] This embodiment also provides a voltage regulation device for a photovoltaic inverter, which is used to implement the above embodiments and preferred embodiments; details already described will not be repeated. As used below, the terms "module" and "device" can refer to a combination of software and / or hardware that performs a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0202] According to an embodiment of this application, an apparatus embodiment for implementing a voltage regulation method for a photovoltaic inverter is also provided. Figure 3 This is a schematic diagram of a voltage regulation device for a photovoltaic inverter according to an embodiment of this application, as shown below. Figure 3 As shown, the voltage regulation device of the photovoltaic inverter includes a data acquisition module 302, a first determination module 304, a second determination module 306, a third determination module 308, and a fourth determination module 310. The device will be described below.

[0203] The data acquisition module 302 is used to acquire the historical reactive power and willingness level of the target photovoltaic inverter in the target area, the load current corresponding to multiple harmonics of the load in the target area in the current cycle, and the voltage corresponding to multiple harmonics of the grid connection point of the target area in the current cycle. The willingness level is used to characterize the degree to which the user corresponding to the target photovoltaic inverter is willing to respond to the voltage regulation command.

[0204] The first determining module 304, connected to the data acquisition module 302, is used to determine the energy command and harmonic commands corresponding to multiple harmonics of the target photovoltaic inverter in the current cycle based on historical reactive power and desired level. The energy command is used to indicate the upper limit of the total electrical energy that the target photovoltaic inverter can consume in the current cycle, and the harmonic command is used to indicate the upper limit of the harmonic current amplitude of the corresponding harmonic that the target photovoltaic inverter can inject in the current cycle.

[0205] The second determining module 306, connected to the first determining module 304, is used to determine the initial virtual admittance of the target photovoltaic inverter in the current cycle based on the load current, voltage, energy command, harmonic command, and willingness level corresponding to the multiple harmonics respectively.

[0206] The third determining module 308, connected to the second determining module 306, is used to determine the target virtual admittance of the target photovoltaic inverter in the current cycle based on the initial virtual admittance corresponding to the multiple harmonics respectively.

[0207] The fourth determining module 310, connected to the third determining module 308, is used to determine the target voltage adjustment command of the target photovoltaic inverter in the current cycle based on the target virtual admittance corresponding to multiple harmonics, and to adjust the output voltage of the target photovoltaic inverter using the target voltage adjustment command.

[0208] This application provides a voltage regulation device for a photovoltaic inverter. By setting a data acquisition module 302, a first determination module 304, a second determination module 306, a third determination module 308, and a fourth determination module 310, the device achieves the purpose of determining the target photovoltaic inverter's energy command and harmonic commands by acquiring the historical reactive power and desired level of the target photovoltaic inverter in the target area, the load current corresponding to the multiple harmonics of the load in the target area, and the voltage corresponding to the multiple harmonics of the grid connection point in the target area. This allows for the determination of the target voltage regulation command of the target photovoltaic inverter, thereby improving the accuracy of the target voltage regulation command determination and improving the voltage regulation quality of the target photovoltaic inverter. This solves the technical problem in related technologies where inaccurate determination of the photovoltaic inverter's voltage regulation command leads to unsatisfactory voltage regulation effects.

[0209] It should be noted that the above modules can be implemented by software or hardware. For example, for the latter, it can be implemented in the following ways: the above modules can be located in the same processor; or the above modules can be located in different processors in any combination.

[0210] It should be noted that the data acquisition module 302, the first determining module 304, the second determining module 306, the third determining module 308, and the fourth determining module 310 mentioned above correspond to steps S102 to S110 in the embodiments. The instances and application scenarios implemented by the above modules and their corresponding steps are the same, but they are not limited to the content disclosed in the above embodiments. It should be noted that the above modules, as part of the device, can run in a computer terminal.

[0211] It should be noted that the optional or preferred implementation methods of this embodiment can be found in the relevant descriptions in the embodiments, and will not be repeated here.

[0212] The voltage regulation device of the aforementioned photovoltaic inverter may also include a processor and a memory. The data acquisition module 302, the first determination module 304, the second determination module 306, the third determination module 308, the fourth determination module 310, etc. are all stored in the memory as program units, and the processor executes the aforementioned program units stored in the memory to realize the corresponding functions.

[0213] The processor contains a core that retrieves the corresponding program unit from memory. One or more cores may be configured. Memory may include non-persistent memory in computer-readable media, random access memory (RAM), and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory includes at least one memory chip.

[0214] This application provides a non-volatile storage medium storing a program that, when executed by a processor, implements a voltage regulation method for a photovoltaic inverter.

[0215] This application provides an electronic device. Figure 4 This is a structural diagram of an electronic device provided according to an embodiment of this application. For example... Figure 4 As shown, the electronic device may include: one or more ( Figure 4 (Only one is shown) a processor 402, a memory 404, a memory controller, and a peripheral interface, wherein the peripheral interface is connected to an RF module, an audio module, and a display. The electronic device includes a processor, a memory, and a program stored in the memory and executable on the processor. When the processor executes the program, it performs the following steps: obtaining the historical reactive power and willingness level of the target photovoltaic inverter in the target area, the load current corresponding to multiple harmonics of the load in the target area in the current cycle, and the voltage corresponding to multiple harmonics of the grid connection point of the target area in the current cycle, wherein the willingness level characterizes the degree to which the user corresponding to the target photovoltaic inverter is willing to respond to voltage regulation commands; based on the historical reactive power and willingness level, determining the energy command and harmonic commands corresponding to multiple harmonics of the target photovoltaic inverter in the current cycle, wherein the energy command indicates the total electrical energy that the target photovoltaic inverter can consume in the current cycle. The upper limit and harmonic command are used to indicate the upper limit of the harmonic current amplitude of the corresponding subharmonic that can be injected into the target photovoltaic inverter in the current cycle. Based on the load current, voltage, energy command, harmonic command, and willingness level corresponding to each harmonic, the initial virtual admittance of the target photovoltaic inverter for each harmonic in the current cycle is determined. Based on the initial virtual admittance of each harmonic, the target virtual admittance of the target photovoltaic inverter for each harmonic in the current cycle is determined. Based on the target virtual admittance of each harmonic, the target voltage regulation command of the target photovoltaic inverter for the current cycle is determined, and the output voltage of the target photovoltaic inverter is regulated using the target voltage regulation command. The device in this article can be a server, PC, etc.

[0216] This application also provides a computer program product, which, when executed on a data processing device, is suitable for executing an initialization program with the following method steps: obtaining the historical reactive power and willingness level of the target photovoltaic inverter in the target area, the load current corresponding to multiple harmonics of the load in the target area in the current cycle, and the voltage corresponding to multiple harmonics of the grid connection point of the target area in the current cycle, wherein the willingness level is used to characterize the degree to which the user corresponding to the target photovoltaic inverter is willing to respond to the voltage regulation command; based on the historical reactive power and willingness level, determining the energy command and harmonic commands corresponding to multiple harmonics of the target photovoltaic inverter in the current cycle, wherein the energy command is used to indicate the total electrical energy that the target photovoltaic inverter can consume in the current cycle. The limit and harmonic command are used to indicate the upper limit of the harmonic current amplitude of the corresponding subharmonic that can be injected into the target photovoltaic inverter in the current cycle. Based on the load current, voltage, energy command, harmonic command, and willingness level corresponding to each harmonic, the initial virtual admittance of the target photovoltaic inverter corresponding to each harmonic in the current cycle is determined. Based on the initial virtual admittance corresponding to each harmonic, the target virtual admittance of the target photovoltaic inverter corresponding to each harmonic in the current cycle is determined. Based on the target virtual admittance corresponding to each harmonic, the target voltage regulation command of the target photovoltaic inverter in the current cycle is determined, and the output voltage of the target photovoltaic inverter is regulated using the target voltage regulation command.

[0217] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0218] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0219] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0220] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0221] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0222] Memory may include non-persistent memory in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0223] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can store information using any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0224] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0225] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0226] The above are merely embodiments of this application and are not intended to limit the scope of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of the claims of this application.

Claims

1. A method of voltage regulation for a photovoltaic inverter, characterized in that, include: The historical reactive power and willingness level of the target photovoltaic inverter in the target area are obtained, the load current corresponding to multiple harmonics of the load in the target area in the current cycle, and the voltage corresponding to multiple harmonics of the grid connection point of the target area in the current cycle. The willingness level is used to characterize the degree to which the user corresponding to the target photovoltaic inverter is willing to respond to the voltage regulation command. Based on the historical reactive power and the willingness level, the energy command and harmonic commands corresponding to multiple harmonics of the target photovoltaic inverter in the current cycle are determined respectively. The energy command is used to indicate the upper limit of the total electrical energy that the target photovoltaic inverter can consume in the current cycle, and the harmonic command is used to indicate the upper limit of the harmonic current amplitude of the corresponding harmonic that the target photovoltaic inverter can inject in the current cycle. Based on the load current corresponding to each of the multiple harmonics, the voltage corresponding to each of the multiple harmonics, the energy command, the harmonic command corresponding to each of the multiple harmonics, and the willingness level, the initial virtual admittance of the target photovoltaic inverter corresponding to each of the multiple harmonics in the current cycle is determined. Based on the initial virtual admittance corresponding to the multiple harmonics, the target virtual admittance of the target photovoltaic inverter corresponding to the multiple harmonics in the current cycle is determined. Based on the target virtual admittance corresponding to the multiple harmonics, the target voltage regulation command of the target photovoltaic inverter in the current cycle is determined, and the output voltage of the target photovoltaic inverter is regulated using the target voltage regulation command.

2. The method of claim 1, wherein, The determination of the energy command and harmonic commands corresponding to multiple harmonics of the target photovoltaic inverter in the current cycle based on the historical reactive power and the willingness level includes: Based on the first reactive power of the first historical period in the historical reactive power, the short-term contribution factor of the target photovoltaic inverter is determined. Based on the second reactive power of the second historical period in the historical reactive power, the medium-term contribution factor of the target photovoltaic inverter is determined, wherein the time length corresponding to the first historical period is less than the time length corresponding to the second historical period. Based on the third reactive power of the third historical period in the historical reactive power, the long-term contribution factor of the target photovoltaic inverter is determined, wherein the time length corresponding to the second historical period is less than the time length corresponding to the third historical period. Based on the short-term contribution factor, the medium-term contribution factor, the long-term contribution factor, and the willingness level, the comprehensive contribution factor of the target photovoltaic inverter in the current period is determined. The energy command is determined based on the comprehensive contribution factor and the total energy command of the target station area in the current cycle; Based on the comprehensive contribution factor and the total harmonic commands corresponding to the multiple harmonics of the target transformer area in the current cycle, the harmonic commands corresponding to the multiple harmonics are determined.

3. The method of claim 2, wherein, The determination of the comprehensive contribution factor of the target photovoltaic inverter in the current period based on the short-term contribution factor, the medium-term contribution factor, the long-term contribution factor, and the willingness level includes: The system acquires the voltage deviation of the grid connection point in the current period, the event flag of the target distribution area in the current period, the equipment life index of the target photovoltaic inverter in the current period, and the preset short-term basic score, preset medium-term basic score and preset long-term basic score of the target photovoltaic inverter. The event flag is used to indicate whether the target distribution area is in a disturbance state in the current period, and the equipment life index is used to quantify the aging degree of the target photovoltaic inverter in the current period. Based on the voltage deviation, the event flag, and the preset short-term baseline score, the initial short-term contribution score of the target photovoltaic inverter is determined. The initial short-term contribution score is corrected using the willingness level to obtain the target short-term contribution score of the target photovoltaic inverter; Based on the equipment lifespan index and the preset mid-term baseline score, the target mid-term contribution score of the target photovoltaic inverter is determined. The preset long-term basic score is determined as the target long-term contribution score of the target photovoltaic inverter. Based on the target short-term contribution score, the target medium-term contribution score, and the target long-term contribution score, determine the short-term weight of the short-term contribution factor of the target photovoltaic inverter in the current period, the medium-term weight of the medium-term contribution factor of the target photovoltaic inverter in the current period, and the long-term weight of the long-term contribution factor of the target photovoltaic inverter in the current period. The comprehensive contribution factor is determined based on the short-term contribution factor, the medium-term contribution factor, the long-term contribution factor, the short-term weight, the medium-term weight, and the long-term weight.

4. The method of claim 1, wherein, The determination of the initial virtual admittance of the target photovoltaic inverter corresponding to the multiple harmonics in the current cycle, based on the load current corresponding to each of the multiple harmonics, the voltage corresponding to each of the multiple harmonics, the energy command, the harmonic command corresponding to each of the multiple harmonics, and the willingness level, includes: Based on the voltages corresponding to the multiple harmonics and the load currents corresponding to the multiple harmonics, a target optimization function is constructed, wherein the target optimization function is used to minimize the sum of the squares of the total harmonic currents at the grid connection point and the virtual admittance adjustment cost of the target photovoltaic inverter; Based on the energy command, a first constraint condition is constructed, wherein the first constraint condition is used to ensure that the active power consumption of the target photovoltaic inverter does not exceed the energy command. Based on the harmonic commands corresponding to the multiple harmonics, second constraint conditions are constructed for each of the multiple harmonics. The second constraint conditions are used to ensure that the amplitude of the initial virtual admittance of the target photovoltaic inverter under the corresponding harmonic does not exceed the virtual admittance threshold determined based on the harmonic command of the corresponding harmonic. Based on the willingness level, third constraints are constructed for each harmonic, wherein the third constraints are used to ensure that the initial virtual admittance of the target photovoltaic inverter under the corresponding harmonic does not exceed the feasible domain of virtual admittance under the corresponding harmonic determined based on the willingness level. Based on the objective optimization function, the first constraint, the second constraint corresponding to each of the multiple harmonics, and the third constraint corresponding to each of the multiple harmonics, the initial virtual admittance corresponding to each of the multiple harmonics is determined.

5. The method of claim 1, wherein, Based on the initial virtual admittance corresponding to each of the multiple harmonics, the target virtual admittance of the target photovoltaic inverter corresponding to each of the multiple harmonics in the current cycle is determined, including: Based on the voltages corresponding to the multiple harmonics and the load currents corresponding to the multiple harmonics, the reference virtual admittances corresponding to the multiple harmonics are determined. Based on the reference virtual admittances corresponding to the multiple harmonics and the initial dual variables corresponding to the multiple harmonics, the initial virtual admittances corresponding to the multiple harmonics are iteratively updated to obtain the updated virtual admittances corresponding to the multiple harmonics. Based on the reference virtual admittance corresponding to each harmonic and the updated virtual admittance corresponding to each harmonic, the initial dual variables corresponding to each harmonic are iteratively updated to obtain the updated dual variables corresponding to each harmonic. Based on the reference virtual admittance corresponding to each harmonic and the updated dual variable corresponding to each harmonic, the updated virtual admittance corresponding to each harmonic is iteratively updated to obtain the updated virtual admittance corresponding to each harmonic. The updated virtual admittances corresponding to the multiple harmonics are updated iteratively until the iteration stop condition is met, thereby obtaining the target virtual admittances corresponding to the multiple harmonics.

6. The method of claim 1, wherein, The step of determining the target voltage regulation command of the target photovoltaic inverter in the current cycle based on the target virtual admittance corresponding to the multiple harmonics includes: Based on the target virtual admittance corresponding to the multiple harmonics, the target virtual impedance of the target photovoltaic inverter corresponding to the multiple harmonics in the current cycle is obtained. Based on the target virtual impedance corresponding to each of the multiple harmonics, and the harmonic current corresponding to each of the multiple harmonics generated by the target photovoltaic inverter in response to the target virtual impedance corresponding to each of the multiple harmonics, the voltage regulation amount corresponding to each of the multiple harmonics of the target photovoltaic inverter in the current period is determined. The target voltage regulation command is determined based on the voltage regulation amounts corresponding to the multiple harmonics and the basic voltage regulation amount of the target photovoltaic inverter in the current cycle.

7. The method according to any one of claims 1 to 6, characterized in that, After adjusting the output voltage of the target photovoltaic inverter using the target voltage adjustment command, the method further includes: Based on the confidence coefficient, incentive coefficient, comprehensive contribution factor, and total regulation benefit of the target photovoltaic inverter in the current period, the regulation benefit of the target photovoltaic inverter in the current period due to its participation in voltage regulation is determined. The confidence coefficient is used to indicate whether the target photovoltaic inverter has successfully responded to the target voltage regulation command, and the incentive coefficient is determined based on the willingness level.

8. A voltage regulating device for a photovoltaic inverter, characterized by include: The data acquisition module is used to acquire the historical reactive power and willingness level of the target photovoltaic inverter in the target area, the load current corresponding to multiple harmonics of the load in the target area in the current cycle, and the voltage corresponding to multiple harmonics of the grid connection point of the target area in the current cycle. The willingness level is used to characterize the degree to which the user corresponding to the target photovoltaic inverter is willing to respond to the voltage regulation command. The first determining module is used to determine the energy command and harmonic commands corresponding to multiple harmonics of the target photovoltaic inverter in the current cycle based on the historical reactive power and the willingness level. The energy command is used to indicate the upper limit of the total electrical energy that the target photovoltaic inverter can consume in the current cycle, and the harmonic command is used to indicate the upper limit of the harmonic current amplitude of the corresponding harmonic that the target photovoltaic inverter can inject in the current cycle. The second determining module is used to determine the initial virtual admittance of the target photovoltaic inverter for each of the multiple harmonics in the current cycle based on the load current corresponding to each of the multiple harmonics, the voltage corresponding to each of the multiple harmonics, the energy command, the harmonic command corresponding to each of the multiple harmonics, and the willingness level. The third determining module is used to determine the target virtual admittance of the target photovoltaic inverter for each of the multiple harmonics in the current cycle based on the initial virtual admittance corresponding to each of the multiple harmonics. The fourth determining module is used to determine the target voltage adjustment command of the target photovoltaic inverter in the current cycle based on the target virtual admittance corresponding to the multiple harmonics, and to adjust the output voltage of the target photovoltaic inverter using the target voltage adjustment command.

9. A non-volatile storage medium, comprising: The non-volatile storage medium stores multiple instructions, which are adapted to be loaded by a processor and executed by the voltage regulation method of the photovoltaic inverter according to any one of claims 1 to 7.

10. An electronic device, comprising: include: One or more processors and a memory, the memory being used to store one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors cause the one or more processors to implement the voltage regulation method for a photovoltaic inverter according to any one of claims 1 to 7.

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