Frequency regulation control method and apparatus, device, and storage medium

Abstract

A frequency regulation control method and apparatus, a device, and a storage medium. The method comprises: according to the frequency at a current moment and the calibration frequency of a wind / photovoltaic grid-connected system, determining the frequency deviation value at the current moment and, according to the frequency at the current moment and the frequency at the previous moment, obtaining a frequency deviation change rate (S110); if the absolute value of the frequency deviation value is greater than the absolute value of a preset frequency regulation threshold value, then, according to the frequency deviation value and the frequency deviation change rate, determining inertia response power (S120); according to the frequency deviation value, the preset frequency regulation threshold value, and a preset system maximum frequency deviation, determining droop response power (S130); according to the state of charge of battery energy storage, the inertia response power, and the droop response power, determining battery energy storage target charging and discharging power (S140); and, according to the battery energy storage target charging and discharging power, regulating the frequency of the system (S150).

Description

Frequency modulation control method, device, equipment and storage medium Technical Field

[0001] The embodiments of the present application relate to the technical field of power grid frequency modulation, for example, to a frequency modulation control method, apparatus, device and storage medium. Background Art

[0002] With the rapid development of today's society, fossil energy consumption has increased dramatically, leading to a shortage of traditional fossil energy and exacerbated environmental pollution. Vigorously developing renewable energy sources, such as wind and solar power, is an effective way to address these issues. However, renewable energy sources such as wind and solar power are characterized by volatility and randomness. Large-scale integration into the grid can lead to reduced power system inertia and weakened frequency regulation capabilities. Typically, wind turbines and photovoltaic arrays operate in maximum power point tracking mode, without reserved power reserve capacity to participate in power system frequency regulation. Therefore, frequency fluctuations under high wind power and photovoltaic penetration are a pressing issue for power systems.

[0003] In recent years, many scholars have conducted relevant research and proposed solutions to address the problem of insufficient system frequency response capability caused by the integration of wind and photovoltaic power generation. The approach is to deviate from the maximum power point of wind and photovoltaic power generation equipment, reserve a certain amount of power reserve, and actively participate in primary frequency regulation. However, reserving power reserves for wind and photovoltaic power generation equipment can lead to serious wind and solar curtailment, resulting in a significant waste of resources. Given the advantages of battery energy storage such as high control accuracy, fast response speed, and easy installation, deploying battery energy storage on the wind and photovoltaic power generation side to participate in the system's primary frequency regulation is an effective way to address this problem. Therefore, how to fully utilize the virtual inertia and primary frequency regulation capabilities of battery energy storage and control battery energy storage to assist wind and photovoltaic power generation grid-connected systems in participating in frequency regulation is of great significance to maintaining the stability of grid-connected systems with high wind and photovoltaic power penetration.

[0004] Summary of the Invention

[0005] The embodiments of the present application provide a frequency modulation control method, apparatus, device and storage medium, which solve the problem of insufficient system inertia response and frequency modulation capability caused by wind and solar power abandonment when renewable energy sources such as wind and solar power participate in frequency modulation in a wind-solar grid-connected system.

[0006] This application provides a frequency modulation control method, comprising:

[0007] Determine the frequency deviation value at the current moment according to the current frequency of the wind-solar grid-connected system and the calibrated frequency of the wind-solar grid-connected system, and obtain the frequency deviation change rate according to the current frequency and the frequency at the previous moment;

[0008] When the absolute value of the frequency deviation value is greater than the absolute value of the preset frequency modulation threshold value, determining the inertia response power according to the absolute value of the frequency deviation value and the absolute value of the frequency deviation change rate;

[0009] Determining the droop response power according to the absolute value of the frequency deviation value, the absolute value of the preset frequency modulation threshold value, and the absolute value of the preset maximum frequency deviation of the wind-solar grid-connected system;

[0010] Obtaining the state of charge of the battery energy storage, and determining the target charge and discharge power of the battery energy storage according to the state of charge of the battery energy storage, the inertia response power, and the droop response power;

[0011] The frequency of the wind-solar grid-connected system is adjusted according to the target charging and discharging power of the battery energy storage.

[0012] The present application provides a frequency modulation control device, which includes:

[0013] a frequency deviation determination module configured to determine a frequency deviation value at a current moment based on the current frequency of the wind-solar grid-connected system and the calibrated frequency of the wind-solar grid-connected system, and to obtain a frequency deviation change rate based on the current frequency and the frequency at a previous moment;

[0014] an inertia response power determining module, configured to determine the inertia response power according to the absolute value of the frequency deviation value and the absolute value of the frequency deviation change rate when the absolute value of the frequency deviation value is greater than the absolute value of a preset frequency modulation threshold;

[0015] a droop response power determination module, configured to determine the droop response power according to the absolute value of the frequency deviation value, the absolute value of the preset frequency modulation threshold, and the absolute value of the preset maximum frequency deviation of the wind-solar grid-connected system;

[0016] a target charge and discharge power determination module, configured to obtain the state of charge of the battery energy storage, and determine the target charge and discharge power of the battery energy storage according to the state of charge of the battery energy storage, the inertia response power, and the droop response power;

[0017] The frequency regulation module is configured to adjust the frequency of the wind-solar grid-connected system according to the target charging and discharging power of the battery energy storage.

[0018] The present application provides an electronic device, comprising:

[0019] at least one processor; and

[0020] a memory communicatively coupled to the at least one processor;

[0021] The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the frequency modulation control method described in any embodiment of the present application.

[0022] The present application provides a computer-readable storage medium, which stores computer instructions. The computer instructions are used to enable a processor to implement the frequency modulation control method described in any embodiment of the present application when executed.

[0023] It should be understood that the content described in this section is not intended to identify key or important features of the embodiments of the present application, nor is it intended to limit the scope of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] The following is a brief introduction to the drawings required for use in the embodiments.

[0025] FIG1 is a flow chart of a frequency modulation control method in Example 1 of the present application;

[0026] FIG2A is a schematic diagram of a membership function of a fuzzy controller in Example 1 of the present application;

[0027] FIG2B is a schematic diagram of a membership function of another fuzzy controller in Example 1 of the present application;

[0028] FIG2C is a schematic diagram of a membership function of another fuzzy controller in Example 1 of the present application;

[0029] FIG3 is a schematic diagram of a frequency modulation control method in Example 1 of the present application;

[0030] FIG4 is a schematic diagram of frequency deviation under a load surge condition in Example 1 of the present application;

[0031] FIG5 is a schematic diagram of frequency deviation under a sudden load reduction condition in Example 1 of the present application;

[0032] FIG6 is a schematic structural diagram of a frequency modulation control device in Example 2 of the present application;

[0033] FIG7 is a schematic structural diagram of an electronic device in Example 3 of the present application. DETAILED DESCRIPTION

[0034] The technical solutions in the embodiments of the present application will be described below with reference to the accompanying drawings in the embodiments of the present application.

[0035] The terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequential order. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in a sequence other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, in addition to the process, method, system, product or equipment comprising a series of steps or units shown in the embodiments of the present application, other processes, methods, systems, products and equipment of this series of steps or units not clearly listed may also be included, or other steps or units inherent to these processes, methods, product systems or equipment.

[0036] It is understandable that before using the technical solutions disclosed in the various embodiments of this disclosure, the type, scope of use, usage scenarios, etc. of the personal information involved in this disclosure should be informed to the user and the user's authorization should be obtained in an appropriate manner in accordance with relevant laws and regulations.

[0037] Example 1

[0038] Figure 1 is a flow chart of a frequency modulation control method in Example 1 of the present application. This embodiment is applicable to the frequency modulation of a wind-solar grid-connected system. The method can be executed by a frequency modulation control device in the embodiment of the present application, which can be implemented in software and / or hardware. As shown in Figure 1, the method specifically includes the following steps:

[0039] S110 , determining a frequency deviation value at a current moment according to the current frequency of the wind-solar grid-connected system and the calibrated frequency of the wind-solar grid-connected system, and obtaining a frequency deviation change rate according to the current frequency and the frequency at a previous moment.

[0040] The current frequency of the wind-solar grid-connected system is obtained through the phase-locked loop, and the frequency deviation value of the wind-solar grid-connected system is calculated according to the current frequency of the wind-solar grid-connected system and the calibrated frequency of the wind-solar grid-connected system. The calculation method can be: Δf=ff fre ;

[0041] Among them, Δf is the frequency deviation value, f is the frequency of the wind-solar grid-connected system at the current moment, and f fre The frequency deviation is the calibration frequency of the wind-solar grid-connected system. The real-time frequency of the wind-solar grid-connected system can be obtained at preset time intervals through a phase-locked loop. Then, the frequency deviation change rate is calculated based on the real-time frequency of the wind-solar grid-connected system obtained at the preset time intervals. That is, the frequency deviation change rate is obtained based on the frequency at the current moment and the frequency at the previous moment. The calculation method can be:

[0042] Among them, f is the frequency of the wind and solar grid-connected system at the current moment, ft-1 is the frequency of the previous moment, Δt is the time interval between the current moment and the previous moment, is the frequency deviation change rate.

[0043] S120 , if the absolute value of the frequency deviation is greater than the absolute value of the preset frequency modulation threshold, determining the inertia response power according to the absolute value of the frequency deviation and the absolute value of the frequency deviation change rate.

[0044] The preset frequency modulation threshold is the preset frequency modulation threshold of the battery energy storage. The inertia response power is the response power of the battery energy storage when performing virtual inertia control.

[0045] If the absolute value of the frequency deviation is greater than the absolute value of the preset frequency regulation threshold, the battery energy storage frequency regulation control is started to make its adaptive charging and discharging participate in the frequency regulation of the wind and solar grid-connected system. For example, if the absolute value of the preset frequency regulation threshold is set to |f lim |=0.033Hz, when the absolute value of the frequency deviation |Δf| is greater than |f lim |, the battery energy storage frequency modulation control is started. At this time, the battery energy storage virtual inertia control participates in the frequency modulation. The battery energy storage is controlled to determine the virtual inertia coefficient according to the absolute value of the frequency deviation and the absolute value of the frequency deviation change rate, and perform a virtual inertia response based on the virtual inertia coefficient and the frequency deviation change rate to obtain the inertia response power.

[0046] Optionally, determining the inertia response power based on the absolute value of the frequency deviation value and the absolute value of the frequency deviation change rate includes: determining a virtual inertia coefficient based on the absolute value of the frequency deviation value and the absolute value of the frequency deviation change rate; and determining the inertia response power based on the virtual inertia coefficient and the frequency deviation change rate.

[0047] The virtual inertia coefficient is adaptively adjusted according to the absolute value of the frequency deviation value and the absolute value of the frequency deviation change rate, wherein the adaptive adjustment process can be implemented by a preset fuzzy controller, and the fuzzy controller obtains the virtual inertia coefficient through adaptive decision making of the absolute value of the frequency deviation value and the absolute value of the frequency deviation change rate of the input wind-solar grid-connected system.

[0048] When battery energy storage charging and discharging participate in system frequency regulation, at the initial stage of frequency regulation startup, during the inertia response phase, the battery energy storage charging and discharging power is mainly controlled by virtual inertia, which regulates the battery energy storage charging and discharging to support the frequency response. The calculation method for determining the inertia response power based on the virtual inertia coefficient and the frequency deviation change rate can be:

[0049] Among them, H I is the virtual inertia coefficient, is the frequency deviation change rate, ΔP Iis the inertia response power.

[0050] By determining a virtual inertia coefficient based on the absolute value of the frequency deviation value and the absolute value of the frequency deviation change rate, and determining the inertia response power based on the virtual inertia coefficient and the frequency deviation change rate, the virtual inertia coefficient can be adaptively determined, and then a rapid response can be achieved based on the virtual inertia coefficient and the frequency deviation change rate to obtain the inertia response power, thereby improving the efficiency and accuracy of obtaining the inertia response power.

[0051] Optionally, the virtual inertia coefficient is determined based on the absolute value of the frequency deviation value and the absolute value of the frequency deviation change rate, including: inputting the absolute value of the frequency deviation value and the absolute value of the frequency deviation change rate into a fuzzy controller, and determining the virtual inertia coefficient based on fuzzy rules in the fuzzy controller; wherein the fuzzy rules of the fuzzy controller include: generating a preset number of fuzzy subsets based on the absolute value of the frequency deviation value and the absolute value of the frequency deviation change rate; determining the fuzzy subset corresponding to the virtual inertia coefficient based on the fuzzy subset corresponding to the absolute value of the frequency deviation value and the fuzzy subset corresponding to the absolute value of the frequency deviation change rate; determining the virtual inertia coefficient based on the fuzzy subset corresponding to the virtual inertia coefficient, the absolute value of the frequency deviation value, and the absolute value of the frequency deviation change rate.

[0052] The preset number of fuzzy subsets can be set according to actual needs. For example, the number of fuzzy subsets can be set to 7, and the fuzzy subsets are NB, NM, NS, ZO, PS, PM, and PB, which respectively represent very small, small, small, medium, large, large, and very large.

[0053] The method of determining the fuzzy subset corresponding to the virtual inertia coefficient according to the fuzzy subset corresponding to the absolute value of the frequency deviation value and the fuzzy subset corresponding to the absolute value of the frequency deviation change rate can be: according to the fuzzy subset corresponding to the absolute value of the frequency deviation value, the fuzzy subset corresponding to the absolute value of the frequency deviation change rate, the membership function of the corresponding relationship between the input (absolute value of the frequency deviation value and the absolute value of the frequency deviation change rate) and the output (virtual inertia coefficient) of the fuzzy controller, and the fuzzy controller logic rule table, the fuzzy subset corresponding to the virtual inertia coefficient is determined. For example, Figures 2A-2C are schematic diagrams of the membership function of the fuzzy controller in Example 1 of the present application. The membership function of the corresponding relationship between the input and output of the fuzzy controller is shown in Figure 2. Figure 2A is the membership of the absolute value of the frequency deviation value, Figure 2B is the membership of the absolute value of the frequency deviation change rate, and Figure 2C is the membership of the virtual inertia coefficient. The fuzzy controller logic rule table is shown in Table 1:

[0054] Table 1 Fuzzy controller logic rules table

[0055] The absolute value of the frequency deviation, the absolute value of the frequency change rate, and the virtual inertia coefficient input to the fuzzy controller all contain seven fuzzy subsets: NB, NM, NS, ZO, PS, PM, and PB. When determining the virtual inertia coefficient using the fuzzy rules of the fuzzy controller, the fuzzy rules must be clear: when the absolute value of the input system frequency deviation is very small and the absolute value of the frequency change rate is very large, the output virtual inertia coefficient is very large; when the absolute value of the input system frequency deviation is small and the absolute value of the frequency change rate is large, the output virtual inertia coefficient is large; when the absolute value of the input system frequency deviation is large and the absolute value of the frequency change rate is small, the output virtual inertia coefficient is small; and when the absolute value of the input system frequency deviation is very large and the absolute value of the frequency change rate is very small, the output virtual inertia coefficient is very small.

[0056] The method for determining the virtual inertia coefficient based on the fuzzy subset corresponding to the virtual inertia coefficient, the absolute value of the frequency deviation value, and the absolute value of the frequency deviation change rate can be: the fuzzy controller presets the weight of the absolute value of the frequency deviation value and the weight of the absolute value of the frequency deviation change rate based on the fuzzy subset corresponding to the virtual inertia coefficient, the absolute value of the frequency deviation value, and the absolute value of the frequency deviation change rate, and then the fuzzy controller decides the virtual inertia coefficient based on the fuzzy subset corresponding to the virtual inertia coefficient, the weight of the absolute value of the frequency deviation value, and the weight of the absolute value of the frequency deviation change rate.

[0057] By inputting the absolute value of the frequency deviation value and the absolute value of the frequency deviation change rate into a fuzzy controller and determining the virtual inertia coefficient according to the fuzzy rules in the fuzzy controller, the virtual inertia coefficient can be quickly determined through the frequency deviation value and the frequency deviation change rate, which can better adapt to the operating environment of different wind-solar grid-connected systems, enhance the adaptability and flexibility of the virtual inertia coefficient, and improve the robustness and reliability of the wind-solar grid-connected systems.

[0058] S130 , determining a droop response power according to an absolute value of the frequency deviation value, an absolute value of a preset frequency modulation threshold, and an absolute value of a preset maximum frequency deviation of the wind-solar grid-connected system.

[0059] The droop response power is the power response when the battery energy storage performs virtual droop control. The preset maximum frequency deviation of the wind-solar grid-connected system can be set according to actual needs.

[0060] When the battery energy storage control frequency is in the primary frequency regulation response stage, the charging and discharging power of the battery energy storage is controlled mainly by virtual droop control, supplemented by virtual inertia control. At this time, the virtual droop control adjusts the charging and discharging of the battery energy storage to support the frequency response. The virtual droop coefficient is determined by the preset virtual droop coefficient analytical model based on the absolute value of the frequency deviation value, the absolute value of the preset frequency regulation threshold value, and the absolute value of the preset maximum frequency deviation of the wind and solar grid-connected system. Then, the droop response power is determined based on the virtual droop coefficient and the frequency deviation value.

[0061] Optionally, the droop response power is determined based on the absolute value of the frequency deviation value, the absolute value of the preset frequency modulation threshold, and the absolute value of the preset maximum frequency deviation of the wind-solar grid-connected system, including: inputting the absolute value of the frequency deviation value, the absolute value of the preset frequency modulation threshold, and the absolute value of the preset maximum frequency deviation of the wind-solar grid-connected system into a virtual droop coefficient analytical model to obtain a virtual droop coefficient; and determining the droop response power based on the virtual droop coefficient and the frequency deviation value.

[0062] Wherein, the virtual droop coefficient analytical model is:

[0063] Among them, |Δf| is the absolute value of the frequency deviation, |Δf max | is the absolute value of the maximum frequency deviation of the preset wind-solar grid-connected system, |Δf lim | is the absolute value of the preset frequency modulation threshold, n is the exponent of the analytical model power operation, K D is the virtual droop coefficient. The speed at which the adaptive virtual droop coefficient responds to changes in the absolute value of the frequency deviation is closely related to the value of the exponent n. When n is small and the absolute value of the frequency deviation is small, a small change in the absolute value of the frequency deviation will cause a large change in the virtual droop coefficient. However, when n is small and the absolute value of the frequency deviation is large, a large change in the absolute value of the frequency deviation will cause a small change in the virtual droop coefficient. When n is large and the absolute value of the frequency deviation is small, a small change in the absolute value of the frequency deviation will cause a small change in the virtual droop coefficient. However, when n is large and the absolute value of the frequency deviation is large, a small change in the absolute value of the frequency deviation will cause a large change in the virtual droop coefficient. Considering that when the frequency fluctuation of a wind-solar grid-connected system is small, a large frequency regulation capability is not required, while when the frequency fluctuation is large, a large frequency regulation capability is required, to balance the system's frequency regulation performance and stability, n = 2 can be selected to construct an analytical model for the virtual droop coefficient.

[0064] After determining the virtual droop coefficient analytical model with n=2, the absolute value of the frequency deviation value, the absolute value of the preset frequency regulation threshold value, and the absolute value of the preset maximum frequency deviation of the wind-solar grid-connected system are input into the virtual droop coefficient analytical model to obtain the virtual droop coefficient. The droop response power is then calculated using the frequency deviation value. The calculation method can be: ΔP D =K D Δf;

[0065] Where ΔP D is the droop response power, K D is the virtual droop coefficient.

[0066] By inputting the absolute value of the frequency deviation value, the absolute value of the preset frequency modulation threshold and the absolute value of the preset maximum frequency deviation of the wind-solar grid-connected system into the virtual droop coefficient analytical model, the virtual droop coefficient is obtained. The droop response power is determined according to the virtual droop coefficient and the frequency deviation value. This enables the wind-solar grid-connected system to adaptively adjust the droop response power according to the actual operating status, so that the system has faster response speed and higher stability.

[0067] S140 , obtaining the state of charge of the battery energy storage, and determining the target charge and discharge power of the battery energy storage according to the state of charge of the battery energy storage, the inertia response power, and the droop response power.

[0068] The battery energy storage's state of charge (SOC) is the battery energy storage's state of charge (SOC). The battery energy storage's target charge and discharge power is the battery energy storage's actual charge and discharge power when controlling frequency modulation. When the frequency deviation is positive, the battery energy storage requires charging for frequency modulation; when the frequency deviation is negative, the battery energy storage requires discharging for frequency modulation.

[0069] The target charge and discharge power of the battery energy storage is generated based on the inertia response power and the droop response power. Alternatively, the state of charge of the battery energy storage is obtained, and a charge and discharge correction coefficient is determined based on the state of charge of the battery energy storage. The charge and discharge power generated by the inertia response power and the droop response power is corrected based on the correction coefficient to obtain the target charge and discharge power of the battery energy storage.

[0070] Optionally, the target charge and discharge power of the battery energy storage is determined according to the state of charge of the battery energy storage, the inertia response power and the droop response power, including: determining the battery energy storage reference power according to the inertia response frequency and the droop response frequency; determining a correction coefficient according to the state of charge of the battery energy storage; and determining the target charge and discharge power of the battery energy storage according to the correction coefficient and the battery energy storage reference power.

[0071] The battery energy storage reference power is the result of the virtual inertia control and virtual droop control working together. The battery energy storage reference power is determined based on the inertia response frequency and the droop response frequency. The calculation method can be: ΔP BESS =ΔP I +ΔP D ;

[0072] Where ΔP BESS is the battery energy storage reference power, ΔP I is the inertia response power, ΔP D is the droop response power.

[0073] The correction factor is determined according to the state of charge of the battery energy storage, and the correction factor can be determined in stages according to the state of charge of the battery energy storage.

[0074] The calculation method for determining the target charge and discharge power of battery energy storage based on the correction coefficient and the reference power of battery energy storage can be: ΔP ES =ω·ΔP BESS ;

[0075] Where ΔP ES is the target charge and discharge power of the battery energy storage, ω is the correction coefficient, ΔP BESS It is the reference power of battery energy storage.

[0076] By determining the battery energy storage reference power according to the inertia response frequency and the droop response frequency, determining the correction coefficient according to the state of charge of the battery energy storage, and determining the battery energy storage target charge and discharge power according to the correction coefficient and the battery energy storage reference power, the utilization efficiency and safety of the battery energy storage can be improved, and the service life of the battery energy storage can be extended.

[0077] Optionally, the correction coefficient is determined according to the state of charge of the battery energy storage, including: if the frequency deviation value is greater than the first value, the state of charge of the battery energy storage is greater than or equal to the first value and less than the second value, then the correction coefficient is determined to be the first preset charging value; if the frequency deviation value is greater than the first value, the state of charge of the battery energy storage is greater than or equal to the second value and less than the third value, then the correction coefficient is determined to be the second preset charging value; if the frequency deviation value is greater than the first value, the state of charge of the battery energy storage is greater than or equal to the third value and less than or equal to the fourth value, then the correction coefficient is determined to be the third preset charging value; if the frequency deviation value is less than the first value, the state of charge of the battery energy storage is greater than or equal to the first value and less than the fifth value, then the correction coefficient is determined to be the first preset discharge value; if the frequency deviation value is less than the first value, the state of charge of the battery energy storage is greater than or equal to the fifth value and less than the sixth value, then the correction coefficient is determined to be the second preset discharge value; if the frequency deviation value is less than the first value, the state of charge of the battery energy storage is greater than or equal to the fifth value and less than or equal to the fourth value, then the correction coefficient is determined to be the third preset discharge value.

[0078] The first value, the second value, the third value, the fourth value, the fifth value, and the sixth value can be set according to actual needs, and the first preset charge value, the second preset charge value, the third preset charge value, the first preset discharge value, the second preset discharge value, and the third preset discharge value can be set according to actual needs. Among them, the first value is 0. When the frequency deviation value is greater than the first value, the frequency deviation value is positive and the battery energy storage needs to be charged. When the frequency deviation value is less than the first value, the frequency deviation value is negative and the battery energy storage needs to be discharged.

[0079] For example, under different states of charge of battery energy storage, the correction factor can be expressed as:

[0080] Among them, S soc is the state of charge of the battery energy storage, ω c is the charging correction coefficient, ω d is the discharge correction coefficient, the second value is 0.7, the first preset charging value is 1, the third value is 0.9, the second preset charging value is 0.5, the fourth value is 1, the third preset charging value is 0, the fifth value is 0.1, the first preset discharge value is 0, the sixth value is 0.3, the second preset discharge value is 0.5, and the third preset discharge value is 1.

[0081] By determining the charging correction coefficient and discharging correction coefficient in stages according to the state of charge of the battery energy storage, the charging and discharging efficiency of the battery energy storage can be optimized, the utilization efficiency and endurance of the battery energy storage can be improved, and the target charging and discharging power of the battery energy storage can be adjusted in real time, thereby improving the performance of the system.

[0082] S150, adjusting the frequency of the wind-solar grid-connected system according to the target charging and discharging power of the battery energy storage.

[0083] In the initial stage of frequency regulation startup, the absolute value of the system frequency deviation change rate is relatively large, while the absolute value of the system frequency deviation value is relatively small. At this time, the target charge and discharge power of the battery energy storage is mainly controlled by virtual inertia, supplemented by virtual droop control; as the absolute value of the system frequency deviation value gradually increases, the absolute value of the system frequency deviation change rate decreases accordingly. At this time, the adaptive virtual inertia frequency regulation capability of the battery energy storage gradually weakens, that is, the inertia response frequency decreases, and the adaptive virtual droop frequency regulation capability gradually increases; when the absolute value of the system frequency deviation value gradually increases to a relatively large value or reaches a maximum value, the absolute value of the system frequency deviation change rate is close to zero, and the target charge and discharge power of the battery energy storage is mainly controlled by virtual droop frequency regulation, supplemented by virtual inertia frequency regulation.

[0084] In a specific example, FIG3 is a schematic diagram of a frequency modulation control method in Embodiment 1 of the present application. As shown in FIG3 , battery energy storage needs to be charged and discharged according to a bidirectional direct current / direct current (DC / DC) converter and a bidirectional direct current / alternating current (DC / AC) converter. The control principle of the bidirectional DC / DC converter is as follows:

[0085] Among them, U out is the output voltage of the bidirectional DC / DC converter, U inis the input voltage of the bidirectional DC / DC inverter, and D is the charging duty cycle of the bidirectional DC / DC converter. By adjusting the value of the bidirectional DC / DC converter, the voltage output of the bidirectional DC / DC converter can be changed, thereby adjusting the charging and discharging power of the battery energy storage. In practical applications, the battery energy storage converts DC power to AC power or AC power to DC power through a bidirectional DC / AC converter, participates in the frequency regulation of the wind-solar grid-connected system, obtains the current frequency of the wind-solar grid-connected system, obtains the frequency deviation value and the frequency deviation change rate, and controls the battery energy storage to perform virtual inertia control and virtual droop control through the frequency deviation value and the frequency deviation change rate. At the same time, the target charging and discharging power ΔP is obtained according to the correction coefficient. ES and compared with the actual battery energy storage charge and discharge power ΔP B The difference is then adjusted through a power control loop (Proportional-Integral (PI) control loop) to generate a pulse width modulation (PWM) signal to control the bidirectional DC / DC converter, and then the bidirectional DC / AC converter participates in the frequency regulation of the wind-solar grid-connected system. Comparing the frequency fluctuations of the wind-solar grid-connected system when the system receives a power disturbance with that when the system is equipped with battery energy storage, as shown in Figures 4, 5 and Table 2, Figure 4 is a schematic diagram of the frequency deviation under the load sudden increase condition in Example 1 of the present application, and Figure 5 is a schematic diagram of the frequency deviation under the load sudden decrease condition in Example 1 of the present application, and Table 2 is as follows:

[0086] Table 2 Maximum frequency deviation of wind-solar system when load suddenly changes

[0087] Compared with a wind-solar grid-connected system without battery energy storage for frequency regulation, this embodiment configures battery energy storage for frequency regulation. When the load of the wind-solar grid-connected system suddenly increases, the maximum frequency deviation of the system decreases by 0.09 Hz, and when the load suddenly decreases, the maximum frequency deviation of the system decreases by 0.095 Hz, greatly reducing the system frequency deviation and enhancing the stability of the system.

[0088] The technical solution of this embodiment is to determine the frequency deviation value at the current moment according to the frequency of the wind-solar grid-connected system at the current moment and the calibrated frequency of the wind-solar grid-connected system, and obtain the frequency deviation change rate according to the frequency at the current moment and the frequency at the previous moment; if the absolute value of the frequency deviation value is greater than the absolute value of the preset frequency modulation threshold, the inertia response power is determined according to the absolute value of the frequency deviation value and the absolute value of the frequency deviation change rate; the droop is determined according to the absolute value of the frequency deviation value, the absolute value of the preset frequency modulation threshold and the absolute value of the preset maximum frequency deviation of the wind-solar grid-connected system. response power; obtaining the state of charge of the battery energy storage, and determining the target charge and discharge power of the battery energy storage according to the state of charge of the battery energy storage, the inertia response power, and the droop response power; adjusting the frequency of the wind-solar grid-connected system according to the target charge and discharge power of the battery energy storage, solving the problem of insufficient system inertia response and frequency regulation capability due to wind and solar power abandonment when renewable energy sources such as wind and solar power participate in frequency regulation in the wind-solar grid-connected system, providing inertia and primary frequency regulation capability for the wind-solar grid-connected system, controlling the battery energy storage to assist the wind-solar grid-connected system in quickly adjusting the frequency, and improving the stability of the wind-solar grid-connected system.

[0089] Example 2

[0090] Figure 6 is a schematic diagram of the structure of a frequency modulation control device in Example 2 of the present application. This embodiment is applicable to frequency modulation in wind and solar grid-connected systems. The device can be implemented using software and / or hardware and can be integrated into any device that provides frequency modulation. As shown in Figure 6, the frequency modulation control device includes: a frequency deviation determination module 210, an inertia response power determination module 220, a droop response power determination module 230, a target charge and discharge power determination module 240, and a frequency modulation module 250.

[0091] The frequency deviation determination module 210 is configured to determine the frequency deviation value at the current moment based on the current frequency of the wind-solar grid-connected system and the calibrated frequency of the wind-solar grid-connected system, and obtain the frequency deviation change rate based on the current frequency and the frequency at the previous moment; the inertia response power determination module 220 is configured to determine the inertia response power based on the absolute value of the frequency deviation value and the absolute value of the frequency deviation change rate when the absolute value of the frequency deviation value is greater than the absolute value of the preset frequency modulation threshold; the droop response power determination module 230 is configured to determine the droop response power based on the absolute value of the frequency deviation value, the absolute value of the preset frequency modulation threshold and the absolute value of the preset maximum frequency deviation of the wind-solar grid-connected system; the target charge and discharge power determination module 240 is configured to obtain the state of charge of the battery energy storage, and determine the target charge and discharge power of the battery energy storage based on the state of charge of the battery energy storage, the inertia response power and the droop response power; the frequency modulation module 250 is configured to adjust the frequency of the wind-solar grid-connected system according to the target charge and discharge power of the battery energy storage.

[0092] Optionally, the inertia response power determination module 220 is configured to: determine a virtual inertia coefficient according to an absolute value of the frequency deviation value and an absolute value of a frequency deviation change rate; and determine an inertia response power according to the virtual inertia coefficient and the frequency deviation change rate.

[0093] Optionally, the droop response power determination module 230 is configured to: input the absolute value of the frequency deviation value, the absolute value of the preset frequency modulation threshold, and the absolute value of the preset maximum frequency deviation of the wind-solar grid-connected system into a virtual droop coefficient analytical model to obtain a virtual droop coefficient; and determine the droop response power based on the virtual droop coefficient and the frequency deviation value.

[0094] Optionally, the virtual droop coefficient analytical model is:

[0095] Among them, |Δf| is the absolute value of the frequency deviation, |Δf max | is the absolute value of the maximum frequency deviation of the preset wind-solar grid-connected system, |Δf lim | is the absolute value of the preset frequency modulation threshold, n is the exponent of the analytical model power operation, K D is the virtual droop coefficient.

[0096] Optionally, the target charge and discharge power determination module 240 is configured to: determine the battery energy storage reference power based on the inertia response frequency and the droop response frequency; determine a correction coefficient based on the state of charge of the battery energy storage; and determine the battery energy storage target charge and discharge power based on the correction coefficient and the battery energy storage reference power.

[0097] Optionally, the inertia response power determination module 220 is configured to determine the virtual inertia coefficient in the following manner: inputting the absolute value of the frequency deviation value and the absolute value of the frequency deviation change rate into a fuzzy controller, and determining the virtual inertia coefficient according to fuzzy rules in the fuzzy controller; wherein the fuzzy rules of the fuzzy controller include: generating a preset number of fuzzy subsets according to the absolute value of the frequency deviation value and the absolute value of the frequency deviation change rate; determining the fuzzy subset corresponding to the virtual inertia coefficient according to the fuzzy subset corresponding to the absolute value of the frequency deviation value and the fuzzy subset corresponding to the absolute value of the frequency deviation change rate; and determining the virtual inertia coefficient according to the fuzzy subset corresponding to the virtual inertia coefficient, the absolute value of the frequency deviation value, and the absolute value of the frequency deviation change rate.

[0098] Optionally, the target charge and discharge power determination module 240 is configured to determine the correction coefficient in the following manner: when the frequency deviation value is greater than the first value and the state of charge of the battery energy storage is greater than or equal to the first value and less than the second value, determining the correction coefficient to be the first preset charging value; when the frequency deviation value is greater than the first value and the state of charge of the battery energy storage is greater than or equal to the second value and less than the third value, determining the correction coefficient to be the second preset charging value; when the frequency deviation value is greater than the first value and the state of charge of the battery energy storage is greater than or equal to the third value and less than or equal to the fourth value, determining the correction coefficient to be the third preset charging value; when the frequency deviation value is less than the first value and the state of charge of the battery energy storage is greater than or equal to the first value and less than the fifth value, determining the correction coefficient to be the first preset discharging value; when the frequency deviation value is less than the first value and the state of charge of the battery energy storage is greater than or equal to the fifth value and less than the sixth value, determining the correction coefficient to be the second preset discharging value; when the frequency deviation value is less than the first value and the state of charge of the battery energy storage is greater than or equal to the fifth value and less than the fourth value, determining the correction coefficient to be the third preset discharging value.

[0099] The above-mentioned product can execute the method provided in any embodiment of this application, and has the corresponding functional modules and effects of the execution method.

[0100] Example 3

[0101] FIG7 is a schematic diagram of the structure of an electronic device in Example 3 of the present application. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present application described and / or required herein.

[0102] As shown in Figure 7, the electronic device 10 includes at least one processor 11, and a memory connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., wherein the memory stores a computer program that can be executed by the at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 to the random access memory (RAM) 13. Various programs and data required for the operation of the electronic device 10 can also be stored in the RAM 13. The processor 11, ROM 12 and RAM 13 are connected to each other via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0103] Multiple components in the electronic device 10 are connected to the I / O interface 15, including an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a magnetic disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks.

[0104] The processor 11 can be a variety of general-purpose and / or specialized processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various processors that run machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as the frequency modulation control method.

[0105] In some embodiments, the frequency modulation control method can be implemented as a computer program that is tangibly contained in a computer-readable storage medium, such as the storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed on the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the frequency modulation control method described above can be performed. Alternatively, in other embodiments, the processor 11 can be configured to perform the frequency modulation control method in any other appropriate manner (e.g., by means of firmware).

[0106] Various embodiments of the systems and techniques described herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include being implemented in one or more computer programs that are executable and / or interpreted on a programmable system that includes at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0107] Computer programs for implementing the methods of the present application may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when the computer program is executed by the processor, the functions / operations specified in the flowcharts and / or block diagrams are implemented. The computer program may be executed entirely on the machine, partially on the machine, as a stand-alone software package, partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0108] In the context of the present application, a computer-readable storage medium can be a tangible medium that can contain or store a computer program for use by an instruction execution system, device or equipment or used in combination with an instruction execution system, device or equipment. A computer-readable storage medium can include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium can be a machine-readable signal medium. A machine-readable storage medium can include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM) or a flash memory, an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0109] To provide for user interaction, the systems and techniques described herein may be implemented on an electronic device 10 having: a display device (e.g., a cathode ray tube (CRT) or a liquid crystal display (LCD) monitor) configured to display information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device 10. Other types of devices may also be configured to provide for user interaction; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic input, voice input, or tactile input.

[0110] The systems and techniques described herein can be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with embodiments of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0111] A computing system may include a client and a server. The client and server are generally remote from each other and typically interact via a communication network. The client-server relationship arises through computer programs running on the respective computers and establishing a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, a host product within a cloud computing service ecosystem that addresses the management difficulties and limited scalability of traditional physical hosts and virtual private server (VPS) services.

[0112] It should be understood that the various forms of the processes shown above can be used to reorder, add, or delete steps. For example, the steps described in this application can be performed in parallel, sequentially, or in a different order, as long as the desired results of the technical solution of this application can be achieved. This is not limited herein.

Claims

1. A frequency modulation control method, including: Determine the frequency deviation value at the current moment according to the frequency at the current moment of the wind-solar grid-connected system and the calibrated frequency of the wind-solar grid-connected system, and obtain the frequency deviation change rate according to the frequency at the current moment and the frequency at the previous moment; When the absolute value of the frequency deviation value is greater than the absolute value of the preset frequency modulation threshold, determine the inertia response power according to the absolute value of the frequency deviation value and the absolute value of the frequency deviation change rate; Determine the droop response power according to the absolute value of the frequency deviation value, the absolute value of the preset frequency modulation threshold, and the absolute value of the preset maximum frequency deviation of the wind-solar grid-connected system; Obtain the state of charge of the battery energy storage, and determine the target charge-discharge power of the battery energy storage according to the state of charge of the battery energy storage, the inertia response power, and the droop response power; Adjust the frequency of the wind-solar grid-connected system according to the target charge-discharge power of the battery energy storage.

2. The method according to claim 1, wherein, Determining the inertia response power according to the absolute value of the frequency deviation value and the absolute value of the frequency deviation change rate includes: Determine the virtual inertia coefficient according to the absolute value of the frequency deviation value and the absolute value of the frequency deviation change rate; Determine the inertia response power according to the virtual inertia coefficient and the frequency deviation change rate.

3. The method according to claim 1, wherein, Determining the droop response power according to the absolute value of the frequency deviation value, the absolute value of the preset frequency modulation threshold, and the absolute value of the preset maximum frequency deviation of the wind-solar grid-connected system includes: Input the absolute value of the frequency deviation value, the absolute value of the preset frequency modulation threshold, and the absolute value of the preset maximum frequency deviation of the wind-solar grid-connected system into the virtual droop coefficient analysis model to obtain the virtual droop coefficient; Determine the droop response power according to the virtual droop coefficient and the frequency deviation value.

4. The method according to claim 3, wherein, The virtual droop coefficient analysis model is as follows: where |Δf| is the absolute value of the frequency deviation value, |Δf max | is the absolute value of the maximum frequency deviation of the preset wind-solar grid-connected system, |Δf lim | is the absolute value of the preset frequency modulation threshold, n is the exponent of the power operation of the analytical model, and K D is the virtual droop coefficient.

5. The method according to claim 1, wherein, Determining the target charge-discharge power of the battery energy storage according to the state of charge of the battery energy storage, the inertia response power, and the droop response power includes: Determine the reference power of the battery energy storage according to the inertia response frequency and the droop response frequency; Determine the correction coefficient according to the state of charge of the battery energy storage; Determine the target charge-discharge power of the battery energy storage according to the correction coefficient and the reference power of the battery energy storage.

6. The method according to claim 2, wherein, Determining the virtual inertia coefficient according to the absolute value of the frequency deviation value and the absolute value of the frequency deviation change rate includes: Input the absolute value of the frequency deviation value and the absolute value of the frequency deviation change rate into the fuzzy controller, and determine the virtual inertia coefficient according to the fuzzy rules in the fuzzy controller; wherein, the fuzzy rules of the fuzzy controller include: Generate a preset number of fuzzy subsets according to the absolute value of the frequency deviation value and the absolute value of the frequency deviation change rate; Determine the fuzzy subset corresponding to the virtual inertia coefficient according to the fuzzy subset corresponding to the absolute value of the frequency deviation value and the fuzzy subset corresponding to the absolute value of the frequency deviation change rate; Determine the virtual inertia coefficient according to the fuzzy subset corresponding to the virtual inertia coefficient, the absolute value of the frequency deviation value, and the absolute value of the frequency deviation change rate.

7. The method according to claim 5, wherein, determining a correction factor according to the state of charge of the battery energy storage includes: when the frequency deviation value is greater than a first value, and the state of charge of the battery energy storage is greater than or equal to a first value and less than a second value, determining the correction factor as a first preset charging value; when the frequency deviation value is greater than the first value, and the state of charge of the battery energy storage is greater than or equal to the second value and less than a third value, determining the correction factor as a second preset charging value; when the frequency deviation value is greater than the first value, and the state of charge of the battery energy storage is greater than or equal to the third value and less than or equal to a fourth value, determining the correction factor as a third preset charging value; when the frequency deviation value is less than the first value, and the state of charge of the battery energy storage is greater than or equal to the first value and less than a fifth value, determining the correction factor as a first preset discharging value; when the frequency deviation value is less than the first value, and the state of charge of the battery energy storage is greater than or equal to the fifth value and less than a sixth value, determining the correction factor as a second preset discharging value; when the frequency deviation value is less than the first value, and the state of charge of the battery energy storage is greater than or equal to the fifth value and less than or equal to the fourth value, determining the correction factor as a third preset discharging value.

8. A frequency modulation control device, comprising: a frequency deviation determination module configured to determine a frequency deviation value at the current moment according to the frequency at the current moment of the wind-solar grid-connected system and the calibrated frequency of the wind-solar grid-connected system, and obtain a frequency deviation change rate according to the frequency at the current moment and the frequency at the previous moment; an inertia response power determination module configured to determine an inertia response power according to the absolute value of the frequency deviation value and the absolute value of the frequency deviation change rate when the absolute value of the frequency deviation value is greater than the absolute value of a preset frequency modulation threshold; a droop response power determination module configured to determine a droop response power according to the absolute value of the frequency deviation value, the absolute value of the preset frequency modulation threshold, and the absolute value of the maximum frequency deviation of the preset wind-solar grid-connected system; a target charge-discharge power determination module configured to obtain the state of charge of the battery energy storage, and determine a target charge-discharge power of the battery energy storage according to the state of charge of the battery energy storage, the inertia response power, and the droop response power; a frequency modulation module configured to adjust the frequency of the wind-solar grid-connected system according to the target charge-discharge power of the battery energy storage.

9. An electronic device, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein, the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the frequency modulation control method according to any one of claims 1-7.

10. A computer-readable storage medium storing computer instructions for causing a processor to execute the frequency modulation control method according to any one of claims 1-7 when executed.

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