Wind-solar-storage collaborative frequency modulation method based on FUZZY control

Abstract

The invention discloses a wind-light storage collaborative frequency modulation method based on FUZZY control. A wind-light storage collaborative primary frequency modulation strategy of differential FUZZY control is adopted according to different frequency deviation conditions. Firstly, a system frequency deviation range is analyzed, if the system frequency deviation range is within an allowable range, MPPT working condition operation is kept, the frequency deviation working condition is divided into two different conditions of being higher than a frequency upper limit and being lower than a frequency allowable lower limit, and if the frequency is higher than the frequency upper limit, the maximum power point is kept. On the basis of effectively measuring local wind-light-electricity permeability, wind-light conditions and frequency change rate and change frequency of a new energy power station, virtual inertia is estimated, and a virtual inertia FUZZY control logic method determined by different wind-light permeability and wind speed illumination intensity intervals is constructed; and for the condition that the frequency is lower than the lower limit, a storage battery output constraint and FUZZY control logic method is constructed according to the SOC state of the energy storage battery.

Description

Technical Field

[0001] The present invention relates to a method for coordinated frequency regulation of wind, light and energy storage, and particularly to a method for coordinated frequency regulation of wind, light and energy storage based on FUZZY control. Background Art

[0002] With the increasing penetration ratio of new energy power stations in the power grid in our country, the problem of insufficient virtual inertia in the power grid becomes increasingly prominent. Traditional thermal power can cope with the frequency fluctuations caused by factors such as load in the power grid through the large amount of mechanical inertia contained in the rotor, delay the rate of change of frequency, and play a role in stabilizing the power grid frequency. However, new energy power generation has problems such as uncertainty and volatility, and there is actually no inertia. In the prior art, in engineering, the concept of virtual inertia is often extended by cooperating new energy equipment with power electronic equipment to improve the ability of the new energy system to face the challenge of system frequency fluctuations. However, the output of new energy is affected by factors such as the environment. For example, when regulating the frequency of wind power, the wind speed needs to be considered, and when regulating the frequency of a photovoltaic power station, the photovoltaic intensity at different times needs to be considered. At the same time, in order to maintain the economy of the operation of the wind and light power stations, it is necessary to maintain the MPPT operating condition as much as possible. Therefore, how to reasonably allocate energy storage resources on the basis of making full use of the frequency regulation potential of the wind and light power stations, and how to estimate the virtual inertia, so as to effectively improve the primary frequency regulation ability of the system, are technical problems to be solved urgently. Summary of the Invention

[0003] Object of the Invention: Aiming at the above problems, the present invention proposes a method for coordinated frequency regulation of wind, light and energy storage based on FUZZY control, which improves the primary frequency regulation ability of the system and reasonably allocates energy storage resources on the basis of making full use of the frequency regulation potential of the wind and light power stations.

[0004] Technical Solution: The technical solution adopted by the present invention is a method for coordinated frequency regulation of wind, light and energy storage based on FUZZY control, which performs coordinated frequency regulation of wind, light and energy storage according to the real-time power grid frequency deviation and load conditions, including:

[0005] If the frequency deviation is within the frequency dead zone range and the system load decreases, the MPPT operating condition is maintained;

[0006] If the frequency deviation is higher than the upper limit of the frequency dead zone range, the frequency regulation output of the wind and light system is obtained through the FUZZY control logic method determined by the wind-light penetration rate, wind speed and light intensity interval;

[0007] If the frequency deviation is lower than the lower limit of the frequency dead zone range and the system load increases, the frequency regulation output of the energy storage system is obtained through the energy storage output constraint and the FUZZY control logic method determined by the penetration rate and SOC of the energy storage battery.

[0008] The FUZZY control logic method determined by the wind-solar penetration rate, wind speed, and light intensity range includes: obtaining the frequency modulation distribution coefficients of the wind turbine and photovoltaic according to the wind-solar penetration rate, wind speed, and light intensity through the FUZZY control logic method; obtaining the droop fuzzy control parameters and virtual inertia fuzzy control parameters of the wind turbine and photovoltaic according to the frequency deviation and the rate of change of frequency through the FUZZY control logic method; and finally calculating the frequency modulation output of the wind turbine and photovoltaic according to the frequency deviation and the frequency modulation distribution coefficients, droop fuzzy control parameters, and virtual inertia fuzzy control parameters of the wind turbine and photovoltaic.

[0009] The frequency modulation output of the wind turbine and photovoltaic is calculated according to the frequency deviation and the frequency modulation distribution coefficients, droop fuzzy control parameters, and virtual inertia fuzzy control parameters of the wind turbine and photovoltaic. The calculation formula is:

[0010] ΔP W =-K W G W (s)Δf(s)

[0011] ΔP PV =-K PV G PV (s)Δf(s)

[0012] G W (s)=K Wp s+K Wd

[0013] G PV (s)=K PVp s+K PVd

[0014] K Wd =30α d ,K Wp =30α p

[0015] K PVd =30α d ,K PVp =30α p

[0016] In the formula, ΔP W is the frequency modulation output of the wind turbine, ΔP PV is the frequency modulation output of the photovoltaic, K w is the frequency modulation distribution coefficient of the wind turbine, K pv is the frequency modulation distribution coefficient of the photovoltaic, G W (s) is the open-loop transfer function of the virtual inertia frequency modulation controller of the wind turbine, G PV (s) is the open-loop transfer function of the virtual inertia frequency modulation controller of the photovoltaic, Δf(s) is the frequency deviation in the frequency domain, s represents the variable calculated in the frequency domain, KWp is the virtual inertia coefficient of the fan, K Wd is the droop control coefficient of the fan, K PVp is the virtual inertia coefficient of the PV generator, K PVd is the PV droop control coefficient, α d are the droop fuzzy control parameters and the virtual inertia fuzzy control parameters.

[0017] There are the following constraints for the frequency modulation distribution coefficients of the fan and PV:

[0018] K W +K PV = 1

[0019] In the formula, K w is the frequency modulation distribution coefficient of the fan, K pv is the frequency modulation distribution coefficient of the PV.

[0020] For heavy load conditions, the wind-solar system operates in the MPPT mode, and the energy storage system is put into frequency modulation; the FUZZY control logic method determined by the penetration rate and SOC of the energy storage battery includes:

[0021] Calculate the SOC of the energy storage battery;

[0022] According to the penetration rate and SOC of the energy storage battery, obtain the frequency modulation distribution coefficient of the energy storage system through the FUZZY control logic method;

[0023] According to the frequency modulation distribution coefficient of the energy storage system and the frequency deviation, calculate the frequency modulation output of the energy storage system. The calculation formula is:

[0024] P ref_BESS = K BESS G c (s)Δf(s)

[0025] G c (s)= -k pf / (T c s + 1)

[0026] In the formula, P ref_BESS is the frequency modulation output of the energy storage system, K BESS is the frequency modulation distribution coefficient of the energy storage system; Δf(s) is the frequency deviation in the frequency domain; G c (s) is the frequency characteristic control function of the energy storage system; k pf is the primary frequency modulation coefficient; T c is the response time constant of the energy storage itself.

[0027] The calculation formula for the SOC of the energy storage battery is:

[0028] S SOC = S0 - (1 / Q n)∫P ES dt

[0029] where S SOC is the SOC of the energy storage battery, and S0 is the initial value of the SOC of the energy storage battery; Q n is the rated capacity of the energy storage; P ES is the charging and discharging power of the energy storage, which is positive during discharging and negative during charging; t is time.

[0030] The energy storage output constraint is as follows:

[0031] P A = P m + P BESS

[0032] where P A is the load of the system, P BESS is the compensation power provided by the energy storage system; P m is the mechanical power provided under the maximum power tracking of the wind turbine.

[0033] The present invention provides a computer device, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, the above-mentioned coordinated frequency modulation method for wind-solar-energy storage based on FUZZY control is implemented.

[0034] The present invention provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the above-mentioned coordinated frequency modulation method for wind-solar-energy storage based on FUZZY control is implemented.

[0035] The present invention provides a computer program product, including a computer program / instructions. When the computer program / instructions are executed by a processor, the above-mentioned coordinated frequency modulation method for wind-solar-energy storage based on FUZZY control is implemented.

[0036] Advantageous effects: Compared with the prior art, the present invention has the following advantages: The wind-solar power station maintains the MPPT working condition for as long as possible, maintaining the economy of long-term operation. When the frequency fluctuation of the system exceeds the dead zone of frequency modulation, it is judged whether the cause of the system frequency fluctuation is due to heavy load or light load, and different frequency modulation strategies are adopted according to different situations. During the frequency modulation process, the frequency modulation distribution ratio between different devices is adjusted according to the new energy penetration rate, considering factors such as wind speed, photovoltaic intensity, and battery SOC, and FUZZY control is used to reasonably control the frequency fluctuation. The present invention effectively improves the primary frequency modulation ability of the system and reasonably allocates energy storage resources on the basis of fully utilizing the frequency modulation potential of the wind-solar power station. Brief Description of the Drawings

[0037] Figure 1 is the primary frequency modulation control block diagram of the wind-solar power station under load shedding disturbance described in the present invention;

[0038] Figure 2 is the primary frequency regulation control block diagram of the storage battery under heavy load disturbance described in the present invention;

[0039] Figure 3 is the membership function of wind power penetration rate;

[0040] Figure 4 is the membership function of wind speed;

[0041] Figure 5 is the membership function of the frequency modulation distribution coefficient of the wind turbine;

[0042] Figure 6 is the membership function of photovoltaic penetration rate;

[0043] Figure 7 is the membership function of irradiation intensity;

[0044] Figure 8 is the membership function of the frequency modulation distribution coefficient of the photovoltaic;

[0045] Figure 9 is the membership function of the frequency deviation of the FUZZY control of the wind-solar power station;

[0046] Figure 10 is the membership function of the frequency change rate of the FUZZY control of the wind-solar power station;

[0047] Figure 11 is the membership function of the droop fuzzy control parameter of the wind-solar power station;

[0048] Figure 12 is the membership function of the virtual inertia fuzzy control parameter of the wind-solar power station;

[0049] Figure 13 is the membership function of the frequency deviation of the FUZZY control of the energy storage system;

[0050] Figure 14 is the membership function of the frequency change rate of the FUZZY control of the energy storage system;

[0051] Figure 15 is the membership function of the droop fuzzy control parameter of the energy storage system;

[0052] Figure 16 is the membership function of the virtual inertia fuzzy control parameter of the energy storage system;

[0053] Figure 17 is the flow chart of the wind-solar-storage collaborative frequency modulation method based on FUZZY control described in the present invention. Detailed implementation manners

[0054] The technical solution of the present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0055] For the wind-solar-storage coordinated frequency modulation method based on FUZZY control of the present invention, the grid frequency offset is measured in real time by a detection device. If the offset is within the frequency dead zone range, the system operates in the MPPT mode to ensure the maximum economic benefit of the wind-solar power plant. If the frequency offset is higher than the frequency modulation dead zone, it is divided into two different situations: higher than the frequency upper limit and lower than the frequency allowable lower limit. For the situation where the frequency is higher than the upper limit, a first FUZZY control logic method for virtual inertia determined by different wind-solar penetration rates and wind speed and light intensity intervals is constructed. For the situation where the frequency is lower than the lower limit, according to the SOC state of the energy storage battery, a battery output power constraint and a second FUZZY control logic method are constructed.

[0056] According to the direction of the frequency offset, two different frequency modulation strategies of wind-solar power station frequency modulation and battery frequency modulation are adopted respectively. The frequency modulation dead zone described in this article is taken as |Δf∣≤R.

[0057] When Δf>R, the system load decreases. At this time, the wind-solar power station mainly participates in frequency modulation. The virtual inertia control additional power ΔP1 and the droop control additional adjustment power ΔP2 obtained according to the frequency deviation Δf are respectively and ΔP2=K p (f n -f s ), and its control block diagram is as Figure 1 shown.

[0058] When Δf<-R, the system load increases. At this time, the wind-solar power station operates in the MPPT mode. The energy storage system is connected to the DC side bus capacitor of the DFIG through an inverter. Calculate the SOC depth of the battery energy storage at this time and reasonably configure the energy storage output. The response of the inverter is at the ms level, and it can effectively withdraw from the primary frequency modulation in time to prevent overshoot. The primary frequency modulation structure of the battery under heavy load disturbance is as Figure 2 shown.

[0059] First, according to the local wind-solar penetration rate, wind speed and irradiance intensity, the FUZZY control method is used to determine the fan frequency modulation distribution coefficient K w and the photovoltaic frequency modulation distribution coefficient K pv . On this basis, FUZZY control is performed on Δf and . When the frequency change exceeds the frequency modulation dead zone, the primary frequency modulation is started. First, consider the light load situation. At this time, the frequency is higher than the allowable value. FUZZY fuzzy control is used for the wind-solar units. Considering different penetration rate fan units and photovoltaic units, reasonable frequency modulation distribution coefficients are adopted in different wind speed intervals and photovoltaic intensity intervals as shown in formulas (1) to (5):

[0060] K W+K PV = 1(1)

[0061] ΔP W = -K W G W (s)Δf(s) (2)

[0062] ΔP PV = -K PV G PV (s)Δf(s) (3)

[0063] G W (s)= K Wp s + K Wd (4)

[0064] G PV (s)= K PVp s + K PVd (5)

[0065] In the formula, K W is the frequency modulation distribution coefficient of the wind turbine, K PV is the frequency modulation distribution coefficient of the photovoltaic generator, ΔP W is the frequency modulation output of the wind turbine, ΔP PV is the frequency modulation output of the photovoltaic generator, K Wp is the virtual inertia coefficient of the wind turbine, K Wd is the droop control coefficient of the wind turbine, K PVp is the virtual inertia coefficient of the photovoltaic generator, K PVd is the droop control coefficient of the photovoltaic generator, G W (s) is the open-loop transfer function of the virtual inertia frequency modulation controller of the wind turbine, G PV (s) is the open-loop transfer function of the virtual inertia frequency modulation controller of the photovoltaic generator. s represents the use of frequency domain calculation, G w and G pv are functions of s.

[0066] Its FUZZY control logic is shown in Tables 1 - 2. The membership functions of the wind power penetration rate are as Figure 3 shown, the membership functions of the wind speed are as Figure 4 shown, and the membership functions of the frequency modulation distribution coefficient of the wind turbine are as Figure 5 shown. The membership functions of the photovoltaic penetration rate are as Figure 6 shown, the membership functions of the irradiation intensity are as Figure 7 shown, and the membership functions of the frequency modulation distribution coefficient of the photovoltaic generator are as Figure 8 shown.

[0067] Table 1 FUZZY Control Logic of the Frequency Modulation Distribution Coefficient of the Wind Turbine

[0068]

[0069] Table 2 FUZZY control logic of photovoltaic frequency modulation distribution coefficient

[0070]

[0071] Assume that the fan and the photovoltaic power station adopt similar virtual frequency modulation and droop control coefficients. Here, the virtual frequency modulation coefficient and the droop control coefficient are also included. First, set the FUZZY control logic considering different Δf and The virtual inertia control coefficients and droop control coefficients of each subsystem are shown in Eqs. (6) to (7):

[0072] K Wd = 30α d , K Wp = 30α p (6)

[0073] K PVd = 30α d , K PVp = 30α p (7)

[0074] In the formula, α d is the droop fuzzy control parameter and α p is the virtual inertia fuzzy control parameter.

[0075] The FUZZY control logic of the droop fuzzy control parameters and virtual inertia fuzzy control parameters of the fan and the photovoltaic power station is shown in Tables 3 to 4. The membership function of the frequency deviation is as Figure 9 shown, the membership function of the frequency change rate is as Figure 10 shown, the membership function of the droop fuzzy control parameter is as Figure 11 shown. The membership function of the virtual inertia fuzzy control parameter is as Figure 12 shown.

[0076] Table 3 FUZZY control logic of the droop fuzzy control coefficient of the fan and the photovoltaic power station

[0077]

[0078]

[0079] Table 4 FUZZY control logic of the virtual inertia fuzzy control parameter of the fan and the photovoltaic power station

[0080]

[0081] When facing the disturbance of increasing load, there is no standby frequency modulation power in the wind-solar power station at this time. At this time, calculate the SOC depth state of the energy storage to determine the frequency modulation output of the battery.

[0082] For the charge and discharge state of the battery, five groups of fuzzy language variables are defined to describe its SOC, namely VL (very low), L (low), M (medium), H (high), and VH (very high). For heavy load conditions, at this time, the wind-solar power station operates in the MPPT mode, and the battery is put into frequency modulation. According to the depth of the battery SOC, the appropriate frequency characteristic control model expression of the energy storage is selected as:

[0083] G c (s)=ΔP c (s) / Δf(s)=-k pf / (T c s + 1)(8)

[0084] Where: ΔP c is the power provided by the energy storage system; Δf(s) is the frequency deviation signal at the input signal end of the power grid based on the droop control strategy of the energy storage system; k pf is the primary frequency modulation coefficient; T c is the response time constant of the energy storage itself. G c (s) represents the change rate of the output of the energy storage system. The SOC of the energy storage battery can be calculated as shown in Equation (9):

[0085] S SOC =S0-(1 / Q n )∫P ES dt(9)

[0086] Where: S0 is the initial value of the SOC of the energy storage battery; Q n is the rated capacity of the energy storage; P ES is the charge and discharge power of the energy storage, which is positive when discharging and negative when charging. After meeting the SOC constraint, the battery energy storage system starts to discharge under droop control, and the reference value of the output power is:

[0087] P ref_BESS =K BESS G c (s)Δf(s)(10)

[0088] Where, K BESS is the frequency modulation distribution coefficient of the battery energy storage system. When the system frequency drops, the battery energy storage system continuously discharges. The battery energy storage is connected to the DC bus capacitor of the doubly-fed wind turbine through a bidirectional DC-DC converter. For the battery, a unified comprehensive inertia parameter α d and α p are used for the frequency response control of the wind-solar-storage unit. The virtual inertia control coefficient and droop control coefficient of each subsystem are shown in Equation (11):

[0089] K Ed =15α d ,K Ep= 10α p (11)

[0090] For the charge and discharge states of the battery, five groups of fuzzy language variables are defined to describe its SOC, namely VL (very low), L (low), M (medium), H (high), and VH (very high). The FUZZY control logics of the frequency modulation distribution coefficient, droop fuzzy control parameter, and virtual inertia fuzzy control parameter of the energy storage system are shown in Tables 5 - 7. The membership function of the frequency deviation of the FUZZY control of the energy storage system is as shown in Figure 13 shown, and the membership function of the rate of change of frequency of the FUZZY control of the energy storage system is as shown in Figure 14 shown. The membership function of the droop fuzzy control parameter of the energy storage system is as shown in Figure 15 shown. The membership function of the virtual inertia fuzzy control parameter of the energy storage system is as shown in Figure 16 shown.

[0091] Table 5 Frequency modulation distribution coefficient of the energy storage system

[0092]

[0093] Table 6 FUZZY control logic of the droop fuzzy control parameter of the energy storage system

[0094]

[0095] Table 7 FUZZY control logic of the virtual inertia fuzzy control parameter of the energy storage system

[0096]

[0097]

[0098] The mechanical power provided by the doubly-fed wind turbine under maximum power tracking and the compensation power provided by the battery through droop control are taken as input quantities, and the load side of the system is the output quantity. At this time, the system energy balance relationship is:

[0099] P A = P m + P BESS (12)

[0100] In the formula, P BESS is the compensation power provided by the energy storage device; P m is the mechanical power output by the wind turbine.

[0101] In summary, the primary frequency regulation strategy of wind-solar-storage based on FUZZY control is as shown in Figure 17 shown.

[0102] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, the above-mentioned FUZZY control-based coordinated frequency regulation method for wind-solar-storage is implemented.

[0103] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the above-mentioned FUZZY control-based coordinated frequency regulation method for wind-solar-storage is implemented.

[0104] In one embodiment, a computer program product is provided, including a computer program / instructions. When the computer program / instructions are executed by a processor, the above-mentioned FUZZY control-based coordinated frequency regulation method is implemented.

[0105] 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 a complete hardware embodiment, a complete 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 memories, CD-ROMs, optical memories, etc.) containing computer-usable program codes.

[0106] The present application is described with reference to the flowcharts and / or block diagrams of methods, devices (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, as well as the combination of flows and / or blocks in the flowchart and / or block diagram, can be implemented 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 a device for implementing the functions specified in Figure 1 one process or multiple processes and / or blocks Figure 1 one block or multiple blocks.

[0107] 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 an instruction device that implements the functions specified in Figure 1 one process or multiple processes and / or blocks Figure 1 one block or multiple blocks.

[0108] These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus, such that the instructions executed on the computer or other programmable apparatus implement a series of operational steps to produce a computer-implemented process, thereby providing steps for implementing the functions specified in one or more processes and / or blocks Figure 1 in one or more processes and / or blocks Figure 1 specified in the flowchart or flowcharts and / or block diagram or block diagrams.

Claims

1. A coordinated frequency regulation method for wind-solar-storage based on FUZZY control, characterized in that, Conduct coordinated frequency regulation of wind-solar-storage according to the real-time power grid frequency deviation and load conditions, including: If the frequency deviation is within the frequency dead zone range and the system load decreases, maintain the operation in the MPPT condition; If the frequency deviation is higher than the upper limit of the frequency dead zone range, obtain the frequency regulation output of the wind-solar system through the FUZZY control logic method determined by the wind-solar penetration rate, wind speed, and light intensity interval; If the frequency deviation is lower than the lower limit of the frequency dead zone range and the system load increases, obtain the frequency regulation output of the energy storage system through the energy storage output constraint and the FUZZY control logic method determined by the penetration rate and SOC of the energy storage battery.

2. The method for coordinated frequency regulation of wind-solar-storage based on FUZZY control according to claim 1, wherein: The FUZZY control logic method determined by the wind-solar penetration rate, wind speed, and light intensity interval includes: obtaining the frequency regulation distribution coefficients of the wind turbine and photovoltaic through the FUZZY control logic method according to the wind-solar penetration rate, wind speed, and light intensity; obtaining the droop fuzzy control parameters and virtual inertia fuzzy control parameters of the wind turbine and photovoltaic through the FUZZY control logic method according to the frequency deviation and frequency change rate; finally, calculating the frequency regulation output of the wind turbine and photovoltaic according to the frequency deviation and the frequency regulation distribution coefficients, droop fuzzy control parameters, and virtual inertia fuzzy control parameters of the wind turbine and photovoltaic.

3. The method for coordinated frequency regulation of wind-solar-storage based on FUZZY control according to claim 1, wherein: Calculate the frequency regulation output of the wind turbine and photovoltaic according to the frequency deviation and the frequency regulation distribution coefficients, droop fuzzy control parameters, and virtual inertia fuzzy control parameters of the wind turbine and photovoltaic. The calculation formula is: ΔP W =-K W G W (s)Δf(s) ΔP PV =-K PV G PV (s)Δf(s) G W (s) = K Wp s + K Wd G PV (s) = K PVp s + K PVd K Wd = 30α d ,K Wp = 30α p K PVd = 30α d ,K PVp = 30α p Where, ΔP W is the frequency modulation output of the fan, and ΔP PV is the frequency modulation output of the PV, K w is the frequency modulation distribution coefficient of the fan, and K pv is the frequency modulation distribution coefficient of the PV, G W (s) is the open-loop transfer function of the virtual inertia frequency modulation controller of the fan, G PV (s) is the open-loop transfer function of the virtual inertia frequency modulation controller of the PV unit, Δf(s) is the frequency deviation in the frequency domain, s represents the variable calculated in the frequency domain, K Wp is the virtual inertia coefficient of the fan, and K Wd is the droop control coefficient of the fan, and K PVp is the virtual inertia coefficient of the PV unit, and K PVd is the droop control coefficient of the PV, α d is the droop fuzzy control parameter and the virtual inertia fuzzy control parameter.

4. The method for coordinated frequency regulation of wind-solar-storage based on FUZZY control according to claim 1, characterized in that: There are the following constraints on the frequency regulation distribution coefficients of the wind turbine and photovoltaic: K W +K PV = 1 Where K w is the frequency modulation distribution coefficient of the fan, and K pv is the frequency modulation distribution coefficient of the photovoltaic.

5. The method for coordinated frequency regulation of wind-solar-storage based on FUZZY control according to claim 1, characterized in that: For heavy load conditions, the wind-solar system maintains the operation in the MPPT condition, and the energy storage system is put into frequency regulation. The FUZZY control logic method determined by the penetration rate and SOC of the energy storage battery includes: Calculate the SOC of the energy storage battery; Obtain the frequency regulation distribution coefficient of the energy storage system through the FUZZY control logic method according to the penetration rate and SOC of the energy storage battery; Calculate the frequency regulation output of the energy storage system according to the frequency regulation distribution coefficient of the energy storage system and the frequency deviation. The calculation formula is: P ref_BESS = K BESS G c (s)Δf(s) G c (s) = -k pf / (T c s + 1) Wherein, P ref_BESS is the frequency regulation output of the energy storage system, and K BESS is the frequency regulation distribution coefficient of the energy storage system; Δf(s) is the frequency deviation in the frequency domain; G c (s) is the frequency characteristic control function of the energy storage system; k pf is the primary frequency regulation coefficient; T c is the response time constant of the energy storage itself.

6. The method for coordinated frequency regulation of wind-solar-storage based on FUZZY control according to claim 1, characterized in that: The calculation formula for the SOC of the energy storage battery is: S SOC = S0 - (1 / Q n ) ∫ P ES dt Wherein, S SOC is the SOC of the energy storage battery, and S0 is the initial value of the SOC of the energy storage battery; Q n is the rated capacity of the energy storage; P ES is the charging and discharging power of the energy storage, which is positive during discharging and negative during charging; t is time.

7. The method for coordinated frequency regulation of wind-solar-storage based on FUZZY control according to claim 1, characterized in that: The energy storage output constraint is: P A = P m + P BESS Where, P A is the load of the system, and P BESS is the compensation power provided by the energy storage system; P m is the mechanical power provided under the maximum power tracking of the wind turbine.

8. A computer device, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, When the processor executes the computer program, it realizes the coordinated frequency regulation method of wind-solar-storage based on FUZZY control described in any one of claims 1 to 7.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it realizes the coordinated frequency regulation method of wind-solar-storage based on FUZZY control described in any one of claims 1 to 7.

10. A computer program product, comprising a computer program and / or instructions, characterized in that, When the computer program and / or instruction is executed by the processor, it realizes the coordinated frequency regulation method of wind-solar-storage based on FUZZY control described in any one of claims 1 to 7.

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