Photovoltaic system adjusting method and device, computer program product and electronic equipment

Abstract

The invention discloses an adjusting method and device of a photovoltaic system, a computer program product and electronic equipment. The method relates to the field of new energy or other related fields, and comprises the following steps: determining a photovoltaic battery pack and a storage battery pack in a photovoltaic system, and constructing an optical storage grid-connected model by using the photovoltaic battery pack and the storage battery pack; under the condition that the optical storage grid-connected model is in a running state, energy storage charge data and illumination data are obtained, a target virtual inertia is determined according to the energy storage charge data and the illumination data, and the target virtual inertia is used for maintaining the stability of the optical storage grid-connected model; and adjusting the photovoltaic system according to the target virtual inertia. According to the invention, the problem of poor stability of the photovoltaic system during operation in the prior art is solved.

Description

Technical Field

[0001] The present application relates to the field of new energy or other related fields. Specifically, it relates to a method and device for adjusting a photovoltaic system, a computer program product, and an electronic device. Background Art

[0002] With the increasing global demand for sustainable energy, solar photovoltaic power generation, due to its clean and renewable characteristics, has occupied an increasingly important position in modern power systems and has become one of the key technologies driving the energy transition. The wide application of photovoltaic systems not only helps reduce dependence on fossil fuels but also significantly reduces greenhouse gas emissions, which is of great significance for environmental protection and addressing climate change. However, the inherent characteristics of photovoltaic systems, such as intermittency (affected by sunlight conditions), uncertainty (affected by weather changes), and the volatility of output power, have brought unprecedented challenges to the stable operation of power systems. Especially in modern power grid systems with a high proportion of photovoltaic penetration, the lack of rotational inertia of traditional synchronous generators means that when the grid encounters load mutations or other disturbances, its frequency stability and dynamic response ability will significantly decline.

[0003] To address this issue, the virtual synchronous generator (VSG: Virtual Synchronous Generator) technology has emerged. By simulating the inertia and damping characteristics of traditional generators, VSG provides virtual inertia support for the power grid, enabling photovoltaic inverters to participate in power grid frequency regulation like synchronous generators, and enabling renewable energy generation devices to simulate the behavior of traditional generators, such as frequency response, power regulation, and reactive power support. Thus, without changing the power grid structure, the overall stability and dynamic response performance of the power system can be improved.

[0004] Although VSG technology has improved the stability of the power grid to a certain extent, its practical application effects are restricted by various factors. It is not only directly affected by light intensity but also indirectly affected by the state of charge of the battery pack (such as SOC: State of Charge) and environmental temperature. Currently, most VSG control strategies focus on the change of a single parameter, such as light intensity or battery SOC, and lack a dynamic adjustment mechanism that comprehensively considers multiple constraints (such as light intensity, temperature, battery SOC, etc.). This limitation leads to restrictions on the adaptability and effectiveness of control strategies in practical applications. For example, under the condition of rapid change in light intensity, if the virtual inertia of VSG is not adjusted in time, it may lead to increased power grid frequency fluctuations; while when the battery SOC is low, if VSG still maintains a high virtual inertia, it may cause the battery to over-discharge, affecting battery life and system stability.

[0005] In the related art, there is a problem of poor stability during the operation of a photovoltaic system, and no effective solution has been proposed yet. Summary of the Invention

[0006] The main objective of this application is to provide an adjustment method, device, computer program product, and electronic device for a photovoltaic system to solve the problem of poor stability during the operation of the photovoltaic system in the related art.

[0007] To achieve the above objective, according to one aspect of this application, an adjustment method for a photovoltaic system is provided. The method includes: determining a photovoltaic battery bank and a storage battery bank in the photovoltaic system, and constructing a photovoltaic-storage grid-connected model using the photovoltaic battery bank and the storage battery bank; when the photovoltaic-storage grid-connected model is in an operating state, obtaining energy storage state-of-charge data and illumination data, and determining a target virtual inertia according to the energy storage state-of-charge data and the illumination data, where the target virtual inertia is used to maintain the stability of the photovoltaic-storage grid-connected model; adjusting the photovoltaic system according to the target virtual inertia.

[0008] Further, constructing a photovoltaic-storage grid-connected model using the photovoltaic battery bank and the storage battery bank includes: determining the DC bus of the photovoltaic system, where the DC bus is used to transmit DC electrical energy; connecting the photovoltaic battery bank in series to the DC bus through a first boost circuit, and connecting the storage battery bank in parallel to the DC bus through a second boost circuit to obtain an initial grid-connected model; setting the control strategy of the initial grid-connected model to a constant DC voltage control strategy to obtain an adjusted grid-connected model; connecting an inverter and a filter circuit to the adjusted grid-connected model to obtain a photovoltaic-storage grid-connected model.

[0009] Further, determining a target virtual inertia according to the energy storage state-of-charge data and the illumination data includes: obtaining M state-of-charge intervals, where each state-of-charge interval is associated with a calculation algorithm, and M is a positive integer; determining a target state-of-charge interval from the M state-of-charge intervals according to the energy storage state-of-charge data, and using the target state-of-charge interval to determine a target calculation algorithm; inputting the energy storage state-of-charge data and the illumination data into the target calculation algorithm, and outputting the target virtual inertia.

[0010] Further, inputting the energy storage state-of-charge data and the illumination data into the target calculation algorithm and outputting the target virtual inertia includes: when the target calculation algorithm is a first calculation algorithm, obtaining a first virtual inertia adjustment coefficient and a minimum energy storage state-of-charge, where the first virtual inertia adjustment coefficient is the algorithm coefficient of the first calculation algorithm; calculating the difference between the energy storage state-of-charge data and the minimum energy storage state-of-charge to obtain a first state-of-charge difference, and calculating the product of the first state-of-charge difference and the first virtual inertia adjustment coefficient to obtain a first state-of-charge product; performing a power calculation using the first state-of-charge product to obtain a first state-of-charge data, and calculating the product of the first state-of-charge data and an initial virtual inertia to obtain the target virtual inertia.

[0011] Further, inputting the energy storage charge data and the light intensity data into a target calculation algorithm to output a target virtual inertia includes: when the target calculation algorithm is a second calculation algorithm, obtaining a second virtual inertia adjustment coefficient and a maximum energy storage charge, where the second virtual inertia adjustment coefficient is the algorithm coefficient of the second calculation algorithm; calculating the difference between the energy storage charge data and the maximum energy storage charge to obtain a second charge difference, and calculating the product of the second charge difference and the negative of the second virtual inertia adjustment coefficient to obtain a second charge product; performing a power calculation using the second charge product to obtain second charge data, and calculating the product of the second charge data and the initial virtual inertia to obtain the target virtual inertia.

[0012] Further, inputting the energy storage charge data and the light intensity data into a target calculation algorithm to output a target virtual inertia includes: when the target calculation algorithm is a third calculation algorithm, obtaining a third virtual inertia adjustment coefficient and a light radiation coefficient in the light intensity data, where the third virtual inertia adjustment coefficient is the algorithm coefficient of the third calculation algorithm; calculating the ratio of the light radiation coefficient to a preset parameter to obtain a first ratio, and performing a power calculation using the first ratio and the third virtual inertia adjustment coefficient to obtain third charge data; calculating the product of the third charge data and the initial virtual inertia to obtain the target virtual inertia.

[0013] Further, the initial virtual inertia is determined by the following method: determining an active power-frequency control equation associated with the photovoltaic system according to the rotor motion of the photovoltaic system, where the active power-frequency control equation is used to characterize the power-frequency relationship of the photovoltaic system during operation; calculating the maximum virtual inertia using the active power-frequency control equation, and controlling a simulation tool to debug the maximum virtual inertia to obtain the initial virtual inertia.

[0014] Further, before adjusting the photovoltaic system according to the target virtual inertia, the method further includes: inputting the target virtual inertia into a voltage-current double closed-loop control component to output an initial signal; performing sinusoidal pulse width modulation on the initial signal to output a modulation signal, and connecting the modulation signal to the photovoltaic-storage grid-connected model.

[0015] To achieve the above object, according to another aspect of the present application, there is provided an adjustment device for a photovoltaic system. The device includes: a determination unit configured to determine a photovoltaic battery pack and a storage battery pack in the photovoltaic system, and construct a photovoltaic-storage grid-connected model using the photovoltaic battery pack and the storage battery pack; an acquisition unit configured to obtain energy storage charge data and light intensity data when the photovoltaic-storage grid-connected model is in an operating state, and determine a target virtual inertia according to the energy storage charge data and the light intensity data, where the target virtual inertia is used to maintain the stability of the photovoltaic-storage grid-connected model; and an adjustment unit configured to adjust the photovoltaic system according to the target virtual inertia.

[0016] According to another aspect of the embodiments of the present invention, there is also provided a computer storage medium for storing a program, wherein when the program runs, it controls the device where the computer storage medium is located to execute an adjustment method for a photovoltaic system.

[0017] According to another aspect of the embodiments of the present invention, there is also provided an electronic device including one or more processors and a memory; computer-readable instructions are stored in the memory, and the processor is configured to run the computer-readable instructions, wherein when the computer-readable instructions run, they execute an adjustment method for a photovoltaic system.

[0018] According to another aspect of the embodiments of the present invention, there is also provided a computer program product including a computer program, wherein when the computer program is executed by a processor, it executes an adjustment method for a photovoltaic system.

[0019] Through the present application, the following steps are adopted: determining a photovoltaic battery pack and a storage battery pack in a photovoltaic system, and constructing a photovoltaic-storage grid-connected model by using the photovoltaic battery pack and the storage battery pack; when the photovoltaic-storage grid-connected model is in an operating state, obtaining energy storage state-of-charge data and illumination data, and determining a target virtual inertia according to the energy storage state-of-charge data and the illumination data, wherein the target virtual inertia is used to maintain the stability of the photovoltaic-storage grid-connected model; adjusting the photovoltaic system according to the target virtual inertia, solving the problem of poor stability during the operation of the photovoltaic system in the related art. By constructing a photovoltaic-storage grid-connected model by using the photovoltaic battery pack and the storage battery pack, determining the target virtual inertia according to the collected energy storage state-of-charge data and illumination data, and finally adjusting the photovoltaic system based on the target virtual inertia, the effect of improving the stability of the photovoltaic system is achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] The drawings constituting a part of the present application are used to provide a further understanding of the present application. The schematic embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation to the present application. In the drawings:

[0021] Figure 1 is a flowchart of an adjustment method for a photovoltaic system provided according to an embodiment of the present application;

[0022] Figure 2 is a comparison of the photovoltaic system frequency changes when the frequency suddenly increases and decreases provided according to an embodiment of the present application Figure 1 ;

[0023] Figure 3 is a comparison of the photovoltaic system frequency changes when the frequency suddenly increases and decreases provided according to an embodiment of the present application Figure 2 ;

[0024] Figure 4 is a schematic diagram of a photovoltaic-storage grid-connected model provided according to an embodiment of the present application;

[0025] Figure 5 It is a schematic diagram of an optional adjustment method of a photovoltaic system provided according to an embodiment of the present application;

[0026] Figure 6 It is a schematic diagram of a photovoltaic system provided according to an embodiment of the present application;

[0027] Figure 7 It is a schematic diagram of an adjustment device of a photovoltaic system provided according to an embodiment of the present application;

[0028] Figure 8 It is a schematic diagram of an electronic device provided according to an embodiment of the present application. Detailed implementation manners

[0029] It should be noted that, without conflict, the embodiments in the present application and the features in the embodiments may be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in conjunction with the embodiments.

[0030] In order to enable those skilled in the art to better understand the solution of 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 in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present application.

[0031] It should be noted that the terms "first", "second", etc. in the description and claims of the present invention and the above-mentioned drawings 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 may be interchanged under appropriate circumstances so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device that includes a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0032] It should be noted that the relevant information (including but not limited to user equipment information, user personal information, etc.) and data (including but not limited to data for display, data for analysis, etc.) involved in the present disclosure are all information and data authorized by the user or fully authorized by all parties. For example, an interface is provided between the present system and relevant users or institutions. Before obtaining relevant information, a request for obtaining information needs to be sent to the aforementioned user or institution through the interface, and after receiving the consent information feedback from the aforementioned user or institution, the relevant information can be obtained.

[0033] It should be noted that the information collected in this application is information and data authorized by the user or fully authorized by all parties. Moreover, for the processing of relevant data such as collection, storage, use, processing, transmission, provision, disclosure, and application, all comply with the relevant laws, regulations, and standards of the relevant regions, necessary confidentiality measures are taken, it does not violate public order and good customs, and a corresponding operation entry is provided for users to choose to authorize or refuse to use.

[0034] The present invention will be described below in conjunction with the preferred implementation steps. Figure 1 is a flowchart of a method for adjusting a photovoltaic system according to an embodiment of the present application, as Figure 1 shown, the method includes the following steps:

[0035] Step S101, determine the photovoltaic battery bank and the battery bank in the photovoltaic system, and construct a photovoltaic-storage grid-connected model using the photovoltaic battery bank and the battery bank.

[0036] Specifically, since the output power of the photovoltaic system is affected by various factors such as light intensity, temperature, and the state of the energy storage battery, it is impossible to guarantee the frequency stability of the power grid. In order to improve the dynamic response and stability of the system, an adaptive virtual inertia can be used for control. First, a photovoltaic-storage grid-connected model can be constructed using the photovoltaic battery bank and the battery bank in the photovoltaic system, and then the virtual inertia can be calculated based on this photovoltaic-storage grid-connected model.

[0037] Step S102, when the photovoltaic-storage grid-connected model is in an operating state, obtain the energy storage charge data and the light data, and determine the target virtual inertia according to the energy storage charge data and the light data, where the target virtual inertia is used to maintain the stability of the photovoltaic-storage grid-connected model.

[0038] Specifically, after running the photovoltaic-storage grid-connected model, the SOC value of the energy storage charge data and the light data can be obtained based on this model, and then the virtual inertia can be calculated based on these data. That is, by controlling the magnitude and change rate of the virtual inertia, the photovoltaic-storage grid-connected model can be kept stable in the face of external disturbances, and in the case of insufficient light or insufficient energy storage supply, the virtual inertia can be adjusted to balance the energy supply and demand of the system and ensure the normal operation of the system.

[0039] Step S103, adjust the photovoltaic system according to the target virtual inertia.

[0040] Specifically, after inputting the calculated target virtual inertia into the photovoltaic system, it can help improve the frequency stability of the photovoltaic system and reduce the amplitude of frequency fluctuations. Figure 2 is a comparison of the frequency changes of the photovoltaic system when the frequency suddenly increases and decreases according to an embodiment of the present application Figure 1 , Figure 3It is a comparison of the frequency change of the photovoltaic system when the frequency suddenly increases and decreases provided by the embodiments of the present application Figure 2 , such as Figure 2 , Figure 3 shown, compared with the control strategy of the virtual inertia with constant control, the active power output and the change amount of the frequency of the battery pack controlled by the target virtual inertia are relatively small, the change range is relatively small, the dynamic response performance of the system is improved, and the working condition of the battery pack can be improved.

[0041] The adjustment method of the photovoltaic system provided by the embodiments of the present application determines the photovoltaic battery pack and the battery energy storage pack in the photovoltaic system, and constructs a photovoltaic-battery energy storage grid-connected model by using the photovoltaic battery pack and the battery energy storage pack; when the photovoltaic-battery energy storage grid-connected model is in an operating state, obtains the energy storage state of charge data and the illumination data, and determines the target virtual inertia according to the energy storage state of charge data and the illumination data, where the target virtual inertia is used to maintain the stability of the photovoltaic-battery energy storage grid-connected model; adjusts the photovoltaic system according to the target virtual inertia, solves the problem of poor stability existing during the operation of the photovoltaic system in the related art, constructs a photovoltaic-battery energy storage grid-connected model by using the photovoltaic battery pack and the battery energy storage pack, determines the target virtual inertia according to the collected energy storage state of charge data and the illumination data, and finally adjusts the photovoltaic system based on the target virtual inertia, thereby achieving the effect of improving the stability of the photovoltaic system.

[0042] Figure 4 It is a schematic diagram of the model of the photovoltaic-battery energy storage grid-connected model provided by the embodiments of the present application, such as Figure 4 shown. Optionally, in the adjustment method of the photovoltaic system provided by the embodiments of the present application, constructing a photovoltaic-battery energy storage grid-connected model by using the photovoltaic battery pack and the battery energy storage pack includes: determining the DC bus of the photovoltaic system, where the DC bus is used to transmit DC electric energy; connecting the photovoltaic battery pack in series to the DC bus through a first boost circuit, connecting the battery energy storage pack in parallel to the DC bus through a second boost circuit to obtain an initial grid-connected model; setting the control strategy of the initial grid-connected model as a constant DC voltage control strategy to obtain an adjusted grid-connected model; connecting an inverter and a filter circuit to the adjusted grid-connected model to obtain a photovoltaic-battery energy storage grid-connected model.

[0043] Specifically, the first boost circuit can be a maximum power point tracking (MPPT) boost circuit, and the second boost circuit can be a bidirectional boost circuit. When constructing a photovoltaic (PV) - battery integrated grid - connection model using a PV battery pack and a battery pack, first connect the PV battery pack to a DC bus for transmitting DC (i.e., direct current) electrical energy through the MPPT boost circuit. Then, connect the battery pack (Battery) to the DC bus in parallel through the bidirectional boost circuit, thereby obtaining an initial grid - connection model (i.e., connected to an intermediate DC bus through a DC - DC converter). Next, set the control strategy to a constant DC voltage control strategy, that is, responsible for maintaining the DC voltage at 1000V unchanged. Finally, convert the DC power output from the two battery packs into alternating current (i.e., AC) through an inverter (i.e., a DC - AC converter), and then filter it through a filter circuit to obtain the PV - battery integrated grid - connection model. Finally, it can be connected to a load (represented by a wavy - line symbol) based on this PV - battery integrated grid - connection model. Through constructing the PV - battery integrated grid - connection model in this embodiment, it is possible to stably transmit electrical energy to the power grid based on this model, and at the same time achieve the purpose of energy storage and supply of the PV and energy - storage systems, improving the reliability and efficiency of the PV system.

[0044] Optionally, in the method for adjusting a PV system provided in an embodiment of the present application, determining a target virtual inertia according to energy - storage state - of - charge data and illumination data includes: obtaining M state - of - charge intervals, where each state - of - charge interval is associated with a calculation algorithm, and M is a positive integer; determining a target state - of - charge interval from the M state - of - charge intervals according to the energy - storage state - of - charge data, and using the target state - of - charge interval to determine a target calculation algorithm; inputting the energy - storage state - of - charge data and the illumination data into the target calculation algorithm, and outputting the target virtual inertia.

[0045] Specifically, when calculating the target virtual inertia, since the magnitude of the collected energy - storage state - of - charge data fluctuates, it is first necessary to obtain multiple state - of - charge intervals. For example, the state - of - charge intervals can be [0, 0.2), [0.2, 0.8), and [0.8, 1), and each state - of - charge interval is associated with a calculation algorithm for virtual inertia. Then, select a target state - of - charge interval according to the collected energy - storage state - of - charge data, and then determine the uniquely associated target calculation algorithm according to the target state - of - charge interval. Finally, calculate the target virtual inertia using this calculation algorithm. Through calculating the target virtual inertia using the energy - storage state - of - charge data and the illumination data in this embodiment, it is possible to manage the PV system based on this target virtual inertia, thereby improving the performance and efficiency of the PV system, and also improving the reliability and stability of the system.

[0046] There are various calculation methods for the target virtual inertia. Optionally, in the adjustment method of the photovoltaic system provided in the embodiments of the present application, inputting the energy storage charge data and the light data into the target calculation algorithm, the output of the target virtual inertia includes: when the target calculation algorithm is the first calculation algorithm, obtaining the first virtual inertia adjustment coefficient and the minimum energy storage charge, where the first virtual inertia adjustment coefficient is the algorithm coefficient of the first calculation algorithm; calculating the difference between the energy storage charge data and the minimum energy storage charge to obtain the first charge difference, and calculating the product of the first charge difference and the first virtual inertia adjustment coefficient to obtain the first charge product; performing a power calculation using the first charge product to obtain the first charge data, and calculating the product of the first charge data and the initial virtual inertia to obtain the target virtual inertia.

[0047] Specifically, when calculating the target virtual inertia using the calculation algorithm, if the minimum energy storage charge SOC min is 0.2, when the collected energy storage charge data is in the charge state interval [0, 0.2), the first calculation algorithm can be used to calculate the target virtual inertia. First, the first virtual inertia adjustment coefficient k1 and the minimum energy storage charge SOC min can be obtained, then calculate the difference between the energy storage charge data and the minimum energy storage charge, and calculate the product of the difference and the first virtual inertia adjustment coefficient to obtain the first charge product. Then, perform a power calculation using the first charge product, and finally determine the target virtual inertia based on the product of this data and the initial virtual inertia. The target virtual inertia H can be calculated by the following formula: where k1 represents the first virtual inertia adjustment coefficient, and H0 is the initial virtual inertia constrained by the frequency change rate. In this embodiment, by using different calculation algorithms to calculate the target virtual inertia, the accuracy of the virtual inertia can be improved, and further the stability of the system can be improved.

[0048] Optionally, in the adjustment method of the photovoltaic system provided in the embodiments of the present application, inputting the energy storage charge data and the light data into the target calculation algorithm, the output of the target virtual inertia includes: when the target calculation algorithm is the second calculation algorithm, obtaining the second virtual inertia adjustment coefficient and the maximum energy storage charge, where the second virtual inertia adjustment coefficient is the algorithm coefficient of the second calculation algorithm; calculating the difference between the energy storage charge data and the maximum energy storage charge to obtain the second charge difference, and calculating the product of the second charge difference and the negative of the second virtual inertia adjustment coefficient to obtain the second charge product; performing a power calculation using the second charge product to obtain the second charge data, and calculating the product of the second charge data and the initial virtual inertia to obtain the target virtual inertia.

[0049] Specifically, if the maximum energy storage charge SOC maxis 0.8. When the collected energy storage charge data is in the charge state range [0.8, 1), the second calculation algorithm can be used to calculate the target virtual inertia. At this time, the second virtual inertia adjustment coefficient k3 and the maximum energy storage charge SOC can be obtained max , then calculate the difference between the energy storage charge data and the maximum energy storage charge, and then calculate the product of the difference and the negative of the second virtual inertia adjustment coefficient. Use this product for power calculation, and finally obtain the target virtual inertia based on the product of the calculated data and the initial virtual inertia, that is, the target virtual inertia H can be calculated by the following formula: where k3 represents the second virtual inertia adjustment coefficient, and H0 is the initial virtual inertia constrained by the frequency change rate. By using different calculation algorithms to calculate the target virtual inertia, the accuracy of the virtual inertia can be improved, and then the stability of the system can be improved.

[0050] Optionally, in the adjustment method of the photovoltaic system provided in the embodiments of the present application, inputting the energy storage charge data and the light data into the target calculation algorithm, and outputting the target virtual inertia includes: in the case where the target calculation algorithm is the third calculation algorithm, obtaining the third virtual inertia adjustment coefficient and the light radiation coefficient in the light data, where the third virtual inertia adjustment coefficient is the algorithm coefficient of the third calculation algorithm; calculating the ratio of the light radiation coefficient to the preset parameter to obtain the first ratio, using the first ratio and the third virtual inertia adjustment coefficient for power calculation to obtain the third charge data; calculating the product of the third charge data and the initial virtual inertia to obtain the target virtual inertia.

[0051] Specifically, if the minimum energy storage charge SOC min is 0.2 and the maximum energy storage charge SOC max is 0.8. When the collected energy storage charge data is in the charge state range [0.2, 0.8), the third calculation algorithm can be used to calculate the target virtual inertia. At this time, the third virtual inertia adjustment coefficient k2 and the light radiation coefficient in the light data can be obtained, then calculate the ratio of the light radiation coefficient to the preset parameter, use this ratio and the third virtual inertia adjustment coefficient for power calculation, and finally use the calculated data for multiplication calculation with the initial virtual inertia to obtain the target virtual inertia, that is, the target virtual inertia H can be calculated by the following formula: where I pv is the light radiation coefficient of the photovoltaic system.

[0052] Optionally, in the method for adjusting a photovoltaic system provided in the embodiments of the present application, the initial virtual inertia is determined in the following manner: determining an active power-frequency control equation associated with the photovoltaic system according to the rotor motion of the photovoltaic system, where the active power-frequency control equation is used to characterize the power-frequency relationship of the photovoltaic system during operation; calculating the maximum virtual inertia using the active power-frequency control equation, and controlling a simulation tool to debug the maximum virtual inertia to obtain the initial virtual inertia.

[0053] Specifically, since the increase in virtual inertia can theoretically reduce the frequency fluctuation of the photovoltaic system during the transient process, thereby optimizing the transient response of the system. However, due to the limited capacity of the converter and the adjustable power per unit time of the system, setting the virtual inertia too large will cause the system to be unable to meet the required power demand. In addition, too large a virtual inertia may also cause a decrease in the system's dynamic response speed, an increase in the overshoot, and may trigger oscillation phenomena. Therefore, before calculating the target virtual inertia, it is first necessary to calculate the initial value, that is, to calculate the initial virtual inertia. Since the active power-frequency control of the photovoltaic system is based on the rotor characteristics of the synchronous generator, the relationship between the active power P and the frequency ω can be determined through the rotor motion equation, and then the active power-frequency control equation characterizing the power-frequency relationship of the photovoltaic system during operation can be obtained:

[0054]

[0055] At this time, according to the above active power-frequency control equation, under steady-state conditions, ignoring the role of the damping part, it can be obtained that:

[0056]

[0057] According to the above formula, the maximum virtual inertia can be obtained:

[0058]

[0059] Since the minimum value of the virtual inertia only needs to be positive, the range of the virtual inertia is: 0 < H ≤ H max Finally, a simulation tool can be used to debug the maximum virtual inertia to obtain the initial virtual inertia. In this embodiment, by debugging the maximum virtual inertia, a suitable initial virtual inertia is obtained to ensure the stability and performance of the system during operation.

[0060] Optionally, in the method for adjusting a photovoltaic system provided in the embodiments of the present application, before adjusting the photovoltaic system according to the target virtual inertia, the method further includes: inputting the target virtual inertia into a voltage-current double closed-loop control component to output an initial signal; performing sinusoidal pulse width modulation on the initial signal to output a modulation signal, and connecting the modulation signal to the photovoltaic-storage grid-connected model.

[0061] Specifically, since the photovoltaic system is constructed using a photovoltaic energy storage grid-connected model, after calculating the target virtual inertia, the target virtual inertia needs to be input into the voltage-current double closed-loop control component first, then the output initial signal is subjected to sinusoidal pulse width modulation, and finally the modulated signal is connected to the photovoltaic energy storage grid-connected model, thereby realizing the adjustment of the photovoltaic system.

[0062] It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in a different order than here.

[0063] The embodiment of the present application also provides a method for adjusting a photovoltaic system. Figure 5 It is a schematic diagram of an optional method for adjusting a photovoltaic system provided by the embodiment of the present application. Figure 6 It is a schematic diagram of a photovoltaic system provided by the embodiment of the present application, as Figure 5 、 Figure 6 shown, the method includes:

[0064] In order to improve the dynamic response and stability of the system, control can be based on an adaptive virtual inertia. First, a photovoltaic energy storage grid-connected model can be constructed using the photovoltaic battery pack and the battery pack in the photovoltaic system, that is, the photovoltaic battery pack is connected to the DC bus for transmitting DC electric energy through a maximum power tracking boost circuit, and then the battery pack Battery is connected in parallel to the DC bus through a bidirectional boost circuit, thereby obtaining an initial grid-connected model. Then, the control strategy is set to a constant DC voltage control strategy, that is, it is responsible for maintaining the DC voltage at 1000V unchanged. Finally, the DC electricity output by the two battery packs is inverted into alternating current through an inverter (that is, a DC-AC converter), and then filtered through a filter circuit to obtain the photovoltaic energy storage grid-connected model.

[0065] When calculating the virtual inertia based on the above photovoltaic energy storage grid-connected model, it is also necessary to determine the initial virtual inertia H0 according to the system state, that is, determine the active frequency control equation associated with the photovoltaic system according to the rotor motion of the photovoltaic system, calculate the maximum virtual inertia using this active frequency control equation, and finally control the simulation tool to debug the maximum virtual inertia to obtain the initial virtual inertia H0.

[0066] Since the parameter changes in the battery pack are restricted by the energy storage charge data during the charge and discharge process and change with the SOC value: where S0 is the initial state of charge value, S n represents the rated capacity of the battery, P represents the charge and discharge power, which is negative for charging and positive for discharging. The definition of the charge and discharge state of the battery pack is: when the state of charge (SOC) of the energy storage unit is lower than SOC minWhen it (which can be 20%) is in this range, it is divided into an area where only charging is allowed and discharging is prohibited. At a low SOC threshold, the terminal voltage of the battery pack is relatively sensitive to the charging operation, while discharging may damage it. In the SOC range of 20% to 80%, the change in the terminal voltage of the battery pack is relatively stable, which is an ideal state for charge and discharge operations. In this interval, the battery can effectively store and release energy. As the SOC further increases, its terminal voltage gradually approaches and reaches the charging cut-off voltage. At this time, the charging power demand of the battery pack decreases to avoid overcharging. Due to the bidirectional charge and discharge characteristics of the battery pack, its discharge capacity gradually increases in this interval. When the SOC exceeds SOC max (which can be 80%), the battery pack only discharges and does not charge. The terminal voltage responds rapidly to the decrease in SOC, and above the charging cut-off voltage, the increase in voltage shows an exponential change.

[0067] Therefore, when the energy storage state-of-charge data SOC is collected, judge the relationship between this value and the minimum energy storage state-of-charge SOC min and the maximum energy storage state-of-charge SOC max . Then, based on the relationship, determine the calculation algorithm, and use this calculation algorithm to calculate the target virtual inertia value, that is, it can be calculated by the following formula:

[0068]

[0069] where k1, k2, and k3 are virtual inertia adjustment coefficients, and H0 is the initial virtual inertia constrained by the frequency change rate; I pv is the light radiation coefficient of the photovoltaic system.

[0070] It should be noted that the above system includes: a photovoltaic battery pack and a storage battery pack (i.e., the power supply part in the system), a DC-DC converter (used to adjust the DC voltage output by the photovoltaic battery pack and the storage battery pack to ensure its matching with the voltage of the intermediate DC bus, and can step up or step down the voltage), an intermediate DC bus (serving as a "bridge" for connecting and integrating DC power supplies with different voltage levels, such as the photovoltaic battery pack and the storage battery pack), an SPWM module (i.e., a Space Vector Pulse Width Modulation module, used to control the switches of the inverter to convert DC power into AC power, which can improve the efficiency and quality of power conversion), a voltage-current double closed-loop control module (used to monitor and adjust the output voltage and current to ensure stable power quality and can be used in the control of the inverter), a reference voltage synthesis module (generates an error signal by comparing the set reference voltage with the actual output voltage, thereby adjusting the output of the inverter to make it close to the reference value), a Q-E control module (i.e., a module for comprehensively controlling the State of Charge (SOC) and the output energy (E) of the photovoltaic battery to optimize the utilization and distribution of energy), a PI control module (i.e., a Proportional Integral controller, used to adjust various parameters in the system, such as voltage, current, frequency, etc., to achieve stable output and system balance), a frequency control module (used to control the AC frequency output by the inverter to synchronize it with the grid frequency or maintain it at a set frequency level), and other control modules (for example, multiple PI control modules, used to adjust different circuit parameters, such as voltage regulation, current control, power management, etc., to ensure the overall operation efficiency and stability of the system).

[0071] In this embodiment, a photovoltaic and energy storage grid-connected model is constructed by using a photovoltaic battery pack and a storage battery pack. The target virtual inertia is determined according to the collected energy storage charge data and illumination data. Finally, the photovoltaic system is adjusted based on the target virtual inertia, thereby achieving the effect of improving the stability of the photovoltaic system.

[0072] The embodiment of the present application also provides an adjustment device for a photovoltaic system. It should be noted that the adjustment device for the photovoltaic system in the embodiment of the present application can be used to execute the adjustment method for the photovoltaic system provided in the embodiment of the present application. The adjustment device for the photovoltaic system provided in the embodiment of the present application will be introduced below.

[0073] Figure 7 is a schematic diagram of the adjustment device for the photovoltaic system provided in the embodiment of the present application, as Figure 7 shown, the device includes: a determination unit 70, an acquisition unit 71, and an adjustment unit 72.

[0074] A determination unit 70, configured to determine a photovoltaic battery pack and a storage battery pack in a photovoltaic system, and construct a photovoltaic-storage grid-connected model by using the photovoltaic battery pack and the storage battery pack;

[0075] An acquisition unit 71, configured to, when the photovoltaic-storage grid-connected model is in an operating state, acquire energy storage state-of-charge data and illumination data, and determine a target virtual inertia according to the energy storage state-of-charge data and the illumination data, where the target virtual inertia is used to maintain the stability of the photovoltaic-storage grid-connected model;

[0076] An adjustment unit 72, configured to adjust the photovoltaic system according to the target virtual inertia.

[0077] The adjustment device for a photovoltaic system provided in an embodiment of the present application determines a photovoltaic battery pack and a storage battery pack in the photovoltaic system through a determination unit 70, and constructs a photovoltaic-storage grid-connected model by using the photovoltaic battery pack and the storage battery pack; an acquisition unit 71 acquires energy storage state-of-charge data and illumination data when the photovoltaic-storage grid-connected model is in an operating state, and determines a target virtual inertia according to the energy storage state-of-charge data and the illumination data, where the target virtual inertia is used to maintain the stability of the photovoltaic-storage grid-connected model; an adjustment unit 72 adjusts the photovoltaic system according to the target virtual inertia, solves the problem of poor stability during the operation of the photovoltaic system in the related art, constructs a photovoltaic-storage grid-connected model by using the photovoltaic battery pack and the storage battery pack, determines the target virtual inertia according to the acquired energy storage state-of-charge data and illumination data, and finally adjusts the photovoltaic system based on the target virtual inertia, thereby achieving the effect of improving the stability of the photovoltaic system.

[0078] Optionally, in the adjustment device for a photovoltaic system provided in an embodiment of the present application, the determination unit 70 includes: a first determination module, configured to determine a DC bus of the photovoltaic system, where the DC bus is used to transmit DC electric energy; a first access module, configured to connect the photovoltaic battery pack in series to the DC bus through a first boost circuit, and connect the storage battery pack in parallel to the DC bus through a second boost circuit to obtain an initial grid-connected model; a setting module, configured to set a control strategy of the initial grid-connected model as a constant DC voltage control strategy to obtain an adjusted grid-connected model; a second access module, configured to connect an inverter and a filter circuit to the adjusted grid-connected model to obtain a photovoltaic-storage grid-connected model.

[0079] Optionally, in the adjustment device for a photovoltaic system provided in an embodiment of the present application, the acquisition unit 71 includes: a first acquisition module, configured to acquire M state-of-charge intervals, where each state-of-charge interval is associated with a calculation algorithm, and M is a positive integer; a second determination module, configured to determine a target state-of-charge interval from the M state-of-charge intervals according to the energy storage state-of-charge data, and determine a target calculation algorithm by using the target state-of-charge interval; an input module, configured to input the energy storage state-of-charge data and the illumination data into the target calculation algorithm and output the target virtual inertia.

[0080] Optionally, in the adjustment device of the photovoltaic system provided in the embodiments of the present application, the acquisition unit 71 includes: a second acquisition module, configured to acquire a first virtual inertia adjustment coefficient and a minimum energy storage state of charge when the target calculation algorithm is a first calculation algorithm, where the first virtual inertia adjustment coefficient is the algorithm coefficient of the first calculation algorithm; a first calculation module, configured to calculate a difference between the energy storage state-of-charge data and the minimum energy storage state of charge to obtain a first state-of-charge difference, and calculate a product of the first state-of-charge difference and the first virtual inertia adjustment coefficient to obtain a first state-of-charge product; a second calculation module, configured to perform a power calculation on the first state-of-charge product to obtain first state-of-charge data, and calculate a product of the first state-of-charge data and the initial virtual inertia to obtain the target virtual inertia.

[0081] Optionally, in the adjustment device of the photovoltaic system provided in the embodiments of the present application, the acquisition unit 71 includes: a third acquisition module, configured to acquire a second virtual inertia adjustment coefficient and a maximum energy storage state of charge when the target calculation algorithm is a second calculation algorithm, where the second virtual inertia adjustment coefficient is the algorithm coefficient of the second calculation algorithm; a third calculation module, configured to calculate a difference between the energy storage state-of-charge data and the maximum energy storage state of charge to obtain a second state-of-charge difference, and calculate a product of the second state-of-charge difference and the negative of the second virtual inertia adjustment coefficient to obtain a second state-of-charge product; a fourth calculation module, configured to perform a power calculation on the second state-of-charge product to obtain second state-of-charge data, calculate a product of the second state-of-charge data and the initial virtual inertia to obtain the target virtual inertia.

[0082] Optionally, in the adjustment device of the photovoltaic system provided in the embodiments of the present application, the acquisition unit 71 includes: a fourth acquisition module, configured to acquire a third virtual inertia adjustment coefficient and a light radiation coefficient in the light data when the target calculation algorithm is a third calculation algorithm, where the third virtual inertia adjustment coefficient is the algorithm coefficient of the third calculation algorithm; a fifth calculation module, configured to calculate a ratio of the light radiation coefficient to a preset parameter to obtain a first ratio, and perform a power calculation on the first ratio and the third virtual inertia adjustment coefficient to obtain third state-of-charge data; a sixth calculation module, configured to calculate a product of the third state-of-charge data and the initial virtual inertia to obtain the target virtual inertia.

[0083] Optionally, in the adjustment device of the photovoltaic system provided in the embodiments of the present application, the initial virtual inertia is determined in the following manner: a third determination module, configured to determine an active power-frequency control equation associated with the photovoltaic system according to the rotor movement of the photovoltaic system, where the active power-frequency control equation is used to characterize the power-frequency relationship of the photovoltaic system during operation; a seventh calculation module, configured to calculate the maximum virtual inertia using the active power-frequency control equation, and control a simulation tool to debug the maximum virtual inertia to obtain the initial virtual inertia.

[0084] Optionally, in the adjustment device of the photovoltaic system provided in the embodiments of the present application, the device further includes: an input unit, configured to input a target virtual inertia into a voltage-current double closed-loop control component before adjusting the photovoltaic system according to the target virtual inertia, and output an initial signal; a modulation unit, configured to perform sinusoidal pulse width modulation on the initial signal, output a modulation signal, and connect the modulation signal to a photovoltaic-storage grid-connected model.

[0085] The above-mentioned adjustment device of the photovoltaic system includes a processor and a memory. The above-mentioned determination unit 70, acquisition unit 71, adjustment unit 72, etc. are all stored in the memory as program units, and the processor executes the above program units stored in the memory to implement corresponding functions.

[0086] The processor contains a kernel, and the kernel retrieves the corresponding program units from the memory. One or more kernels can be set, and by adjusting the kernel parameters, the problem of poor stability in the operation of the photovoltaic system in the related art can be solved.

[0087] The memory may include non-permanent memory in a computer-readable medium, in the form of random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM, and the memory includes at least one storage chip.

[0088] The embodiments of the present invention provide a computer storage medium for storing a program, wherein the program, when running, controls the device where the computer storage medium is located to execute an adjustment method for a photovoltaic system.

[0089] Figure 8 is a schematic diagram of an electronic device provided according to an embodiment of the present application, as Figure 8 shown, the embodiments of the present invention provide an electronic device. The electronic device 80 includes a processor, a memory, and a program stored on the memory and executable on the processor. The processor is used to run computer-readable instructions, wherein the computer-readable instructions, when running, execute an adjustment method for a photovoltaic system. The device herein can be a server, a PC, a PAD, a mobile phone, etc.

[0090] The present application also provides a computer program product, including a computer program, and the computer program, when executed by a processor, implements the steps of an adjustment method for a photovoltaic system in various embodiments of the present application.

[0091] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can take the form of an all-hardware embodiment, an all-software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0092] The present application is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to the embodiments of the present application. It should be understood that each flow and / or block in the flowchart and / or block diagram, and the combination of flows and / or blocks in the flowchart and / or block diagram, can be realized by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, such that the instructions executed by the processor of the computer or other programmable data processing devices generate means for implementing the functions specified in Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0093] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, such that the instructions stored in the computer-readable memory generate a manufactured article including instruction means that implement the functions specified in Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0094] These computer program instructions can also be loaded onto a computer or other programmable data processing device, such that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process, and thus the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0095] In a typical configuration, a computing device includes one or more processors (CPUs), an input / output interface, a network interface, and a memory.

[0096] The memory may include non-permanent memory in the form of computer-readable media, random access memory (RAM), and / or non-volatile memory such as read-only memory (ROM) or flash memory (flash RAM). The memory is an example of computer-readable media.

[0097] A computer-readable medium includes both permanent and non-permanent, removable and non-removable media and can implement information storage by any method or technology. The information can be computer-readable instructions, data structures, program modules, 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, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassettes, magnetic tape disk storage or other magnetic storage devices, or any other non-transitory medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer-readable medium does not include transitory computer-readable media such as modulated data signals and carrier waves.

[0098] It should also be noted that the term "comprising", "including" or any other variation thereof is intended to cover non-exclusive inclusion, so that a process, method, article or apparatus comprising a series of elements not only includes those elements but also includes other elements not expressly listed, or also includes elements inherent to such process, method, article or apparatus. Without further limitation, an element defined by the statement "comprising an..." does not exclude the presence of additional identical elements in the process, method, article or apparatus comprising the element.

[0099] The above are only embodiments of the present application and are not intended to limit the present application. For those skilled in the art, various changes and modifications can be made to the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included within the scope of the claims of the present application.

Claims

1. A method for adjusting a photovoltaic system, characterized in that, Including: Determine the photovoltaic battery pack and the battery pack in the photovoltaic system, and construct a photovoltaic-storage grid-connected model by using the photovoltaic battery pack and the battery pack; When the photovoltaic-storage grid-connected model is in an operating state, obtain energy storage charge data and illumination data, and determine a target virtual inertia according to the energy storage charge data and the illumination data, where the target virtual inertia is used to maintain the stability of the photovoltaic-storage grid-connected model; Adjust the photovoltaic system according to the target virtual inertia.

2. The method according to claim 1, wherein Constructing a photovoltaic-storage grid-connected model by using the photovoltaic battery pack and the battery pack includes: Determine the DC bus of the photovoltaic system, where the DC bus is used to transmit DC electric energy; Connect the photovoltaic battery pack in series to the DC bus through a first boost circuit, and connect the battery pack in parallel to the DC bus through a second boost circuit to obtain an initial grid-connected model; Set the control strategy of the initial grid-connected model to a constant DC voltage control strategy to obtain an adjusted grid-connected model; Connect an inverter and a filter circuit to the adjusted grid-connected model to obtain the photovoltaic-storage grid-connected model.

3. The method according to claim 1, characterized in that, Determining a target virtual inertia according to the energy storage charge data and the illumination data includes: Obtain M state of charge intervals, where each state of charge interval is associated with a calculation algorithm, and M is a positive integer; Determine a target state of charge interval from the M state of charge intervals according to the energy storage charge data, and use the target state of charge interval to determine a target calculation algorithm; Input the energy storage charge data and the illumination data into the target calculation algorithm, and output the target virtual inertia.

4. The method according to claim 3, wherein Inputting the energy storage charge data and the illumination data into the target calculation algorithm and outputting the target virtual inertia includes: When the target calculation algorithm is a first calculation algorithm, obtain a first virtual inertia adjustment coefficient and a minimum energy storage charge, where the first virtual inertia adjustment coefficient is the algorithm coefficient of the first calculation algorithm; Calculate the difference between the energy storage charge data and the minimum energy storage charge to obtain a first charge difference, and calculate the product of the first charge difference and the first virtual inertia adjustment coefficient to obtain a first charge product; Perform a power calculation on the first charge product to obtain a first charge data, and calculate the product of the first charge data and an initial virtual inertia to obtain the target virtual inertia.

5. The method according to claim 3, wherein Inputting the energy storage charge data and the illumination data into the target calculation algorithm and outputting the target virtual inertia includes: When the target calculation algorithm is a second calculation algorithm, obtain a second virtual inertia adjustment coefficient and a maximum energy storage charge, where the second virtual inertia adjustment coefficient is the algorithm coefficient of the second calculation algorithm; Calculate the difference between the energy storage charge data and the maximum energy storage charge to obtain a second charge difference, and calculate the product of the second charge difference and the negative of the second virtual inertia adjustment coefficient to obtain a second charge product; Perform a power calculation on the second charge product to obtain a second charge data, calculate the product of the second charge data and the initial virtual inertia to obtain the target virtual inertia.

6. The method according to claim 3, characterized in that, Inputting the energy storage charge data and the illumination data into the target calculation algorithm and outputting the target virtual inertia includes: When the target calculation algorithm is the third calculation algorithm, obtaining a third virtual inertia adjustment coefficient and an illumination radiation coefficient in the illumination data, where the third virtual inertia adjustment coefficient is an algorithm coefficient of the third calculation algorithm; Calculating a ratio of the illumination radiation coefficient to a preset parameter to obtain a first ratio, and performing a power calculation using the first ratio and the third virtual inertia adjustment coefficient to obtain third charge data; Calculating a product of the third charge data and an initial virtual inertia to obtain the target virtual inertia.

7. The method according to claim 4, claim 5 or claim 6, characterized in that The initial virtual inertia is determined by the following method: Determining an active frequency control equation associated with the photovoltaic system according to the rotor movement of the photovoltaic system, where the active frequency control equation is used to characterize the power-frequency relationship of the photovoltaic system during operation; Calculating a maximum virtual inertia using the active frequency control equation, and controlling a simulation tool to debug the maximum virtual inertia to obtain the initial virtual inertia.

8. The method according to claim 1, characterized in that, Before adjusting the photovoltaic system according to the target virtual inertia, the method further includes: Inputting the target virtual inertia into a voltage-current double closed-loop control component and outputting an initial signal; Performing sinusoidal pulse width modulation on the initial signal to output a modulation signal, and connecting the modulation signal to the photovoltaic energy storage grid-connected model.

9. An adjustment device for a photovoltaic system, characterized in that, Including: A determination unit, configured to determine a photovoltaic battery pack and a storage battery pack in the photovoltaic system, and construct a photovoltaic energy storage grid-connected model using the photovoltaic battery pack and the storage battery pack; An acquisition unit, configured to obtain energy storage charge data and illumination data when the photovoltaic energy storage grid-connected model is in an operating state, and determine a target virtual inertia according to the energy storage charge data and the illumination data, where the target virtual inertia is used to maintain the stability of the photovoltaic energy storage grid-connected model; An adjustment unit, configured to adjust the photovoltaic system according to the target virtual inertia.

10. A computer program product comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the adjustment method of the photovoltaic system according to any one of claims 1 to 8.

11. An electronic device, characterized in that, Including one or more processors and a memory, where the memory is used to store one or more programs, and when the one or more programs are executed by the one or more processors, the one or more processors implement the adjustment method of the photovoltaic system according to any one of claims 1 to 8.

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