Fuzzy adaptive control method and system for virtual inertia of power fusion station

Abstract

The invention discloses an electric power fusion station virtual inertia fuzzy adaptive control method and system, and the method comprises the steps: carrying out the sampling of an AC frequency and a DC voltage, and carrying out the normalization processing, and obtaining a normalized AC frequency and a normalized DC voltage; obtaining a normalized alternating current frequency change rate and a normalized direct current voltage change rate according to the sampling values of the alternating current frequency and the direct current voltage; constructing an active power reference equation according to the actual output power, the normalized alternating current frequency, the normalized direct current voltage, the normalized alternating current frequency change rate and the normalized direct current voltage change rate of the interconnector; according to the active power reference equation, in combination with the power transmission limit constraint of the interconnected converter, designing the constraint of a normalized virtual inertia and a normalized virtual capacitance value; fuzzy control is utilized, and according to dynamic changes of input variables, real-time normalized virtual inertia and a normalized virtual capacitance value are obtained. According to the invention, the dynamic and steady-state performance of the power fusion station system can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of electric power fusion stations, and in particular to a virtual inertia fuzzy adaptive control method and system for an electric power fusion station. Background Art

[0002] The power fusion station uses the substation as a carrier, integrating energy storage stations, distributed photovoltaic stations, charging / swapping stations and other energy stations to build a multi-station fusion energy grid. Since the DC distribution system has the advantages of high power quality, convenient access to distributed power sources and energy storage devices, and fewer intermediate conversion links, it can fully make up for the disadvantages of the traditional AC distribution system when combined with the AC distribution system. It has the advantages of high flexibility and strong competitiveness. Therefore, the power fusion station using AC / DC hybrid architecture is widely used.

[0003] In the power fusion station, the interconnected converter is a bridge connecting the AC side and the DC side, and plays the role of power interaction between the AC side and the DC side, so that they can share the load. Usually, the control strategy adopted by the interconnected converter is double droop control, which can make the normalized values ​​of AC frequency and DC voltage equal, so that the power of the load is distributed on both sides according to their respective capacity. However, the double droop control ignores the dynamic characteristics of the subnet, causing the change rate on both sides of the subnet to cross the boundary. At the same time, the AC and DC sides also have a certain inertia. When the inertia on both sides does not match, frequency or voltage oscillation or even system instability will occur. Summary of the invention

[0004] The technical problem to be solved by the present invention is to solve the problem that the change rates at both ends of the AC side and the DC side in the power fusion station cannot be adaptively controlled.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0006] A fuzzy adaptive control method for virtual inertia of an electric power fusion station, comprising:

[0007] Sampling the AC frequency and the DC voltage, and normalizing the sampled values ​​to obtain a normalized AC frequency and a normalized DC voltage;

[0008] According to the sampling values ​​of the AC frequency and the DC voltage, the AC frequency change rate and the DC voltage change rate are obtained, and then normalized to obtain the normalized AC frequency change rate and the normalized DC voltage change rate;

[0009] According to the actual output power, normalized AC frequency, normalized DC voltage, normalized AC frequency change rate and normalized DC voltage change rate of the interconnector, an active power reference equation is constructed;

[0010] According to the active power reference equation and combined with the power transmission limit constraint of the interconnected converter, the constraints of the normalized virtual inertia and normalized virtual capacitance are designed.

[0011] By utilizing fuzzy control, the real-time normalized virtual inertia and normalized virtual capacitance values ​​are obtained according to the dynamic changes of the input variables.

[0012] In one embodiment of the present invention, the normalized AC frequency and the normalized DC voltage are obtained by the following formula:

[0013]

[0014]

[0015] In the formula, ω ac and u dc are the AC bus frequency and DC bus voltage, ω acs and u dcs are the sampling values ​​of AC bus frequency and DC bus voltage respectively, ω a and ω β are the cutoff frequencies of frequency sampling and voltage sampling respectively, s is the differential operator, ω acs.pu and u dcs.pu are the normalized AC frequency and the normalized DC voltage, ω max and ω min The AC frequency ω is ac The corresponding maximum and minimum limit values, u max and u min They are DC voltage u dc The corresponding maximum and minimum limits, ω acN and u dcN They are ω ac and u dc Rated value.

[0016] In one embodiment of the present invention, the normalized AC frequency change rate and the normalized DC voltage change rate are obtained by the following formulas:

[0017]

[0018] Where dω acs / dt and du dcs / dt are the rate of change of AC frequency and DC voltage respectively, and They are respectively expressed as the normalized AC frequency change rate and the normalized DC voltage change rate, (dω ac / dt) limit and dc / dt) limitThey are respectively expressed as the limit value of the AC frequency change rate and the limit value of the DC voltage change rate.

[0019] In one embodiment of the present invention, the active power reference equation is obtained by the following formula:

[0020]

[0021] In the formula is the reference value of the active power of the interconnected converter, P ILC is the active power actually output by the interconnected converter, K is the droop coefficient of the double droop control, J v and C v are the normalized virtual inertia and normalized virtual capacitance, ω acs.pu and u dcs.pu are the normalized AC frequency and the normalized DC voltage, respectively, and They are expressed as the normalized AC frequency change rate and the normalized DC voltage change rate respectively.

[0022] In one embodiment of the present invention, the constraints of the normalized virtual inertia and the normalized virtual capacitance are obtained by the following formula:

[0023]

[0024] Where P ILC.max is the maximum power transmitted by the interconnected converter, J V.max and C V.max are the maximum value of normalized virtual inertia and the maximum value of normalized virtual capacitance, respectively. and They are respectively represented as the normalized values ​​of the limit value of the frequency change rate and the limit value of the voltage change rate, and both of them are 1.

[0025] In one embodiment of the present invention, obtaining real-time normalized virtual inertia and normalized virtual capacitance values ​​includes:

[0026] Determine the capacity ratio λ between the AC and DC sides;

[0027] Select and As input variables, the real-time normalized virtual inertia and normalized virtual capacitance values ​​are used as output variables; where, and They are expressed as the normalized AC frequency change rate and the normalized DC voltage change rate respectively;

[0028] Define fuzzy subsets of input variables and output variables, select membership functions, and set fuzzy rules;

[0029] The input variables are fuzzified by the fuzzy controller, and then sent to the defuzzification module after reasoning through the fuzzy rule statement. The centroid method is used to defuzzify and obtain the value of the output variable.

[0030] In one embodiment of the present invention, the ratio λ of the capacities on both sides of the AC and DC is obtained by the following formula:

[0031]

[0032] Where P acN is the rated power of AC measurement, P dcN Rated power measured for DC.

[0033] In one embodiment of the present invention, the fuzzy rules are obtained through the following table:

[0034]

[0035] Among them, the fuzzy subset of the input variables is {VS, MS, Z, MB, VB}, and the fuzzy subset of the output variables is the same as the fuzzy subset of the input variables; among them, VS, MS, Z, MB, and VB represent "very small", "small", "medium", "large", and "very large", respectively; the membership function is a triangular membership function; the ratio of the variables in the fuzzy subsets of the two input variables is the ratio of the real-time normalized virtual inertia and the normalized virtual capacitance value.

[0036] In one embodiment of the present invention, the obtained real-time normalized virtual inertia and normalized virtual capacitance values ​​are applied and fed back to the inverter control system of the power fusion station.

[0037] The present invention also provides a virtual inertia fuzzy adaptive control system for an electric power fusion station, which uses the above-mentioned virtual inertia fuzzy adaptive control method for an electric power fusion station, including:

[0038] The sampling module is used to sample the AC frequency and the DC voltage, and normalize the sampled values ​​to obtain the normalized AC frequency and the normalized DC voltage;

[0039] The change rate module is used to obtain the AC frequency change rate and the DC voltage change rate according to the sampled values ​​of the AC frequency and the DC voltage, and then perform normalization processing to obtain the normalized AC frequency change rate and the normalized DC voltage change rate;

[0040] An active power module is used to construct an active power reference equation according to the actual output power of the interconnector, the normalized AC frequency, the normalized DC voltage, the normalized AC frequency change rate, and the normalized DC voltage change rate;

[0041] A constraint module is used to design constraints on normalized virtual inertia and normalized virtual capacitance values ​​according to an active power reference equation and in combination with power transmission limit constraints of interconnected converters;

[0042] The adaptive control module is used to obtain the real-time normalized virtual inertia and normalized virtual capacitance values ​​according to the dynamic changes of input variables by using fuzzy control.

[0043] Compared with the prior art, the present invention has the following beneficial effects:

[0044] 1. The present invention introduces the normalized value of the frequency change rate and the voltage change rate on the basis of the dual droop control, which can not only achieve the equality of the normalized value of the frequency and the voltage in the steady state, but also balance the maximum value of the normalized value of the frequency change rate and the voltage change rate according to the capacity on both sides of the AC and DC.

[0045] 2. The present invention provides a virtual inertia adaptive method based on fuzzy control, which not only balances the maximum value of the normalized value of the frequency change rate and the voltage change rate, but also effectively reduces the adjustment time of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 The present invention is a flowchart of a fuzzy adaptive control method for virtual inertia of a power fusion station according to an embodiment of the present invention.

[0047] Figure 2 4 is a control block diagram of an interconnected converter according to an embodiment of the present invention.

[0048] Figure 3 It is a membership function diagram of input and output of an embodiment of the present invention.

[0049] Figure 4 It is a simplified structural topology diagram of a power fusion station according to an embodiment of the present invention.

[0050] FIG5( a ) shows the AC bus frequency and DC bus voltage waveforms using double droop control according to an embodiment of the present invention.

[0051] FIG5( b ) is a waveform of the AC bus frequency change rate and the DC bus voltage change rate using double droop control according to an embodiment of the present invention.

[0052] FIG6( a ) shows the AC bus frequency and DC bus voltage waveforms using fixed normalized virtual inertia and normalized virtual capacitance according to an embodiment of the present invention.

[0053] FIG6( b ) is a waveform of the AC bus frequency change rate and the DC bus voltage change rate using fixed normalized virtual inertia and normalized virtual capacitance according to an embodiment of the present invention.

[0054] FIG. 7( a ) shows the AC bus frequency and DC bus voltage waveforms using fuzzy adaptive normalized virtual inertia and normalized virtual capacitance according to an embodiment of the present invention.

[0055] FIG7( b ) is a waveform of the AC bus frequency change rate and the DC bus voltage change rate using fuzzy adaptive normalized virtual inertia and normalized virtual capacitance according to an embodiment of the present invention.

[0056] FIG8( a ) shows the AC bus frequency and DC bus voltage waveforms when fuzzy adaptive control is used when λ=0.6 according to an embodiment of the present invention.

[0057] FIG8( b ) shows the waveforms of the AC bus frequency change rate and the DC bus voltage change rate when fuzzy adaptive control is used when λ=0.6 according to an embodiment of the present invention.

[0058] Fig. 9 The present invention is a block diagram of a virtual inertia fuzzy adaptive control system for an electric power fusion station according to an embodiment of the present invention. DETAILED DESCRIPTION

[0059] In order to facilitate those skilled in the art to understand the technical solution of the present invention, the technical solution of the present invention is further described in conjunction with the accompanying drawings of the specification.

[0060] The terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features. In the description of this application, the meaning of "plurality" is two or more, unless otherwise clearly and specifically defined.

[0061] See also Figure 1 and Figure 2 As shown, the present invention discloses a virtual inertia fuzzy adaptive control method for an electric power fusion station, comprising the following steps:

[0062] S10, sampling the AC frequency and the DC voltage, and normalizing the sampled values ​​to obtain a normalized AC frequency and a normalized DC voltage.

[0063] In one embodiment of the present invention, the normalized AC frequency and the normalized DC voltage are obtained by the following formula:

[0064]

[0065]

[0066] In the formula, ω ac and u dc are the AC bus frequency and DC bus voltage, ω acs and udcs are the sampling values ​​of AC bus frequency and DC bus voltage respectively, ω a and ω β are the cutoff frequencies of frequency sampling and voltage sampling respectively, s is the differential operator, ω acs.pu and u dcs.pu are the normalized AC frequency and the normalized DC voltage, ω max and ω min The AC frequency ω is ac The corresponding maximum and minimum limit values, u max and u min They are DC voltage u dc The corresponding maximum and minimum limits, ω acN and u dcN They are ω ac and u dc Rated value.

[0067] S20, obtaining the AC frequency change rate and the DC voltage change rate according to the sampled values ​​of the AC frequency and the DC voltage, and then performing normalization processing to obtain a normalized AC frequency change rate and a normalized DC voltage change rate.

[0068] In this embodiment, the normalized AC frequency change rate and the normalized DC voltage change rate are obtained by the following formulas:

[0069]

[0070] Where dω acs / dt and du dcs / dt are the rate of change of AC frequency and DC voltage respectively, and They are respectively expressed as the normalized AC frequency change rate and the normalized DC voltage change rate, (dω ac / dt) limit and dc / dt) limit They are respectively expressed as the limit value of the AC frequency change rate and the limit value of the DC voltage change rate.

[0071] S30, constructing an active power reference equation according to the actual output power of the interconnector, the normalized AC frequency, the normalized DC voltage, the normalized AC frequency change rate, and the normalized DC voltage change rate.

[0072] In this embodiment, the active power reference equation is obtained by the following formula:

[0073]

[0074] In the formula is the reference value of the active power of the interconnected converter, P ILC is the active power actually output by the interconnected converter, K is the droop coefficient of the double droop control, J v and C v are the normalized virtual inertia and normalized virtual capacitance, ω acs.pu and u dcs.pu are the normalized AC frequency and the normalized DC voltage, respectively, and They are expressed as the normalized AC frequency change rate and the normalized DC voltage change rate respectively.

[0075] In this embodiment, the droop coefficient K of the dual droop control is obtained by the following formula:

[0076]

[0077] In the formula, k ac and k dc are the droop coefficients of the AC subnetwork and the DC subnetwork respectively.

[0078] S40, designing constraints on normalized virtual inertia and normalized virtual capacitance values ​​according to an active power reference equation and in combination with power transmission limit constraints of the interconnected converters.

[0079] In this implementation, the constraints of normalized virtual inertia and normalized virtual capacitance are obtained by the following formula:

[0080]

[0081] Where P ILC.max is the maximum power transmitted by the interconnected converter, J V.max and C V.max are the maximum value of normalized virtual inertia and the maximum value of normalized virtual capacitance, respectively. and They are respectively represented as the normalized values ​​of the limit value of the frequency change rate and the limit value of the voltage change rate, and both of them are 1.

[0082] The output variable, normalized virtual inertia J, can be obtained. V The range is [0,J V.max ], output variable, normalized virtual capacitance C V The range is [0,C V.max ].

[0083] S50, using fuzzy control, according to the dynamic change of input variables, obtain the real-time normalized virtual inertia and normalized virtual capacitance values.

[0084] In this embodiment, the normalized virtual inertia J V and the normalized virtual capacitance CV The size of will affect the frequency change rate and voltage change rate, the normalized virtual inertia J V The larger the value, the lower the frequency change rate, the higher the voltage change rate, and the normalized virtual capacitance C V The larger the value, the lower the voltage change rate and the higher the frequency change rate. Therefore, in order to balance the normalized AC frequency change rate and the normalized DC voltage change rate, the ratio of the rated power of the AC and DC sides, or the ratio of the current measurement capacity to the total capacity, must be determined first.

[0085] Specifically, in this embodiment, obtaining the real-time normalized virtual inertia and normalized virtual capacitance value includes:

[0086] S51, determining the capacity ratio λ between the AC and DC sides.

[0087] In this embodiment, the ratio λ of the capacities on both sides of the AC and DC is obtained by the following formula:

[0088]

[0089] Where P acN is the rated power of AC measurement, P dcN Rated power measured for DC.

[0090] S52, select and As input variables, the real-time normalized virtual inertia and normalized virtual capacitance values ​​are used as output variables.

[0091] S53, define fuzzy subsets of input variables and output variables, select membership functions, and set fuzzy rules.

[0092] In this embodiment, the fuzzy subsets of the input variables are first defined as {VS, MS, Z, MB, VB}, and the fuzzy subsets of the output variables are the same as the input variables, where VS, MS, Z, MB, and VB represent "very small", "small", "medium", "large", and "very large", respectively. The membership function diagram of the input and output is shown in FIG. Figure 3 As shown in the figure, the triangular membership function is selected in the present invention because the membership interval of the triangular membership function is clear and the response speed is fast.

[0093] Secondly, and The maximum value of the ratio should be the ratio of the rated capacity of the AC and DC sides, so choose and As input, set the input variable and The domain is [0,1], and the output variable normalized virtual inertia J is set V and the normalized virtual capacitance CV The domain of is [0,1].

[0094] The relationship between input variables and output variables is summarized into fuzzy rules, which are shown in Table 1.

[0095] Table 1J V and C V Fuzzy rule table

[0096]

[0097] The first column on the left in Table 1 is specified as The first line above specifies The middle part is J V / C V .

[0098] Then, the two input quantities are transformed into fuzzy sets according to the membership function graph, because and The range of is already [0,1], and there is no need to multiply the quantization factor. Fuzzy reasoning uses the Mamdani reasoning method. The Mamdani rule is a reasoning method based on the "if-then" rule. The fuzzy variables are reasoned through the fuzzy rules in Table 1 to obtain the output fuzzy subset. Therefore, when the fuzzy quantity of the input variable is different, the fuzzy quantity of the output variable with different output can be obtained according to the fuzzy rules.

[0099] S54, the input variable is fuzzified by the fuzzy controller, and then sent to the defuzzification module after reasoning through the fuzzy rule statement, and the centroid method is used to defuzzify to obtain the value of the output variable.

[0100] In this embodiment, the last step is defuzzification. In order to enable the system to quickly respond to changes in input quantities and give accurate output values ​​in a timely manner, the centroid defuzzification method is used to obtain two output values ​​in the range of [0,1]. V and C V Set the value of J V.max and C V.max To output the scaling factor, the two output values ​​in the range [0,1] need to be multiplied by J respectively. V.max and C V.max , and finally get the actual normalized virtual inertia J V and the normalized virtual capacitance C V The value of .

[0101] Verification Example

[0102] See also Figure 4As shown, in one embodiment of the present invention, in order to verify the effectiveness of the method of the present invention, a simulation model of a power fusion station is built in Matlab / simulink, and the given parameters of the simulation model are shown in Table 2.

[0103] Table 2 Power fusion station simulation model parameters

[0104]

[0105] Power fusion station topology Figure 4 As shown in the figure, the power fusion station adopts an AC / DC architecture, with the DC side replaced by a DC / DC converter and the AC side replaced by a DC / AC converter, where the interconnected converter is a converter used to connect the AC side and the DC side. In order to simulate the power on both sides, the DC / DC converter adopts virtual DC motor control and the DC / AC converter adopts virtual synchronous generator control.

[0106] The control strategy adopted by the interconnected converter is as follows: Figure 2 As shown, it includes a power outer loop and a current inner loop, wherein the power reference value of the active loop is obtained by adding the output powers of the dual droop control and the bidirectional virtual inertia control. The designed fuzzy adaptation collects the frequency change rate and the voltage change rate as the input of the fuzzy control, and the output is the value of the normalized virtual inertia and the normalized virtual capacitance.

[0107] See also Figure 5(a) to Figure 8(b) As shown, in order to verify the effectiveness of the virtual inertia fuzzy adaptive control method of the power fusion station based on the AC / DC hybrid architecture proposed in the present invention, four simulation comparisons under different conditions are set:

[0108] 1) The interconnected converter only adopts dual droop control, and the DC side load is set to 15kW and the AC side load is set to 10kW at 1s.

[0109] 2) The interconnected converter adopts bidirectional virtual inertia control, but the values ​​of normalized virtual inertia and normalized virtual capacitance are fixed. At 1s, the DC side load is set to 15kW and the AC side load is set to 10kW.

[0110] 3) The interconnected converter adopts bidirectional virtual inertia control, and the normalized virtual inertia and normalized virtual capacitance are adaptively controlled based on fuzzy control. At 1s, the DC side load is set to 15kW and the AC side load is set to 10kW.

[0111] 4) The interconnected converter adopts bidirectional virtual inertia control, and the normalized virtual inertia and normalized virtual capacitance adopt adaptive control based on fuzzy control. The rated power of the AC side is changed to 60kW, and λ=0.6. At 1s, the DC side load is set to 15kW and the AC side load is set to 10kW.

[0112] Figure 5(a), 5(b) It shows that when only dual droop control is used, frequency and voltage oscillations will occur, and the rate of change will also exceed the limit value.

[0113] Figure 6(a) , 6(b) It shows that the use of bidirectional virtual inertia control can solve the frequency and voltage oscillation problems, and can balance the maximum normalized values ​​of the frequency change rate and the voltage change rate. However, the use of fixed normalized virtual inertia and normalized virtual capacitance will cause overshoot of the frequency and voltage waveforms, and also increase the adjustment time of the system.

[0114] Figure 7(a) , 7(b) It shows that the use of fuzzy adaptive normalized virtual inertia and normalized virtual capacitance can not only balance the normalized values ​​of the frequency change rate and the voltage change rate, but also solve the overshoot problem of the voltage waveform and reduce the adjustment time of the system.

[0115] Figure 8(a) , 8(b) show and The maximum value can be balanced according to the ratio of AC and DC measurement capacity.

[0116] In summary, the virtual inertia fuzzy adaptive control method of the power fusion station based on the AC / DC hybrid architecture disclosed in the present invention can not only accurately transmit power using the interconnected converter in steady state, but also optimize the dynamic performance of the system. The simulation results verify the effectiveness of the method of the present invention.

[0117] See also Figures 1 to 9 As shown, the present invention also provides a virtual inertia fuzzy adaptive control system for an electric power fusion station, comprising:

[0118] The sampling module 10 is used to sample the AC frequency and the DC voltage, and perform normalization processing on the sampled values ​​to obtain the normalized AC frequency and the normalized DC voltage.

[0119] The change rate module 20 is used to obtain the AC frequency change rate and the DC voltage change rate according to the sampled values ​​of the AC frequency and the DC voltage, and then perform normalization processing to obtain the normalized AC frequency change rate and the normalized DC voltage change rate.

[0120] The active power module 30 is used to construct an active power reference equation according to the actual output power of the interconnector, the normalized AC frequency, the normalized DC voltage, the normalized AC frequency change rate and the normalized DC voltage change rate.

[0121] The constraint module 40 is used to design the constraints of the normalized virtual inertia and the normalized virtual capacitance value according to the active power reference equation and in combination with the power transmission limit constraints of the interconnected converter.

[0122] The adaptive control module 50 is used to obtain the real-time normalized virtual inertia and normalized virtual capacitance values ​​according to the dynamic changes of the input variables by using fuzzy control.

[0123] It is obvious to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential features of the present invention. Therefore, the embodiments should be regarded as exemplary and non-limiting from any point of view, and the scope of the present invention is defined by the appended claims rather than the above description, and it is intended that all changes falling within the meaning and scope of the equivalent elements of the claims are included in the present invention, and any reference numerals in the claims should not be regarded as limiting the claims involved.

[0124] The above-described embodiments merely represent implementation methods of the invention. The protection scope of the present invention is not limited to the above-described embodiments. For those skilled in the art, several modifications and improvements may be made without departing from the concept of the present invention, which all belong to the protection scope of the present invention.

Claims

1. A fuzzy adaptive control method for virtual inertia of an electric power fusion station, characterized in that: include: Sampling the AC frequency and the DC voltage, and normalizing the sampled values ​​to obtain a normalized AC frequency and a normalized DC voltage; According to the sampling values ​​of the AC frequency and the DC voltage, the AC frequency change rate and the DC voltage change rate are obtained, and then normalized to obtain the normalized AC frequency change rate and the normalized DC voltage change rate; According to the actual output power, normalized AC frequency, normalized DC voltage, normalized AC frequency change rate and normalized DC voltage change rate of the interconnector, an active power reference equation is constructed; According to the active power reference equation and combined with the power transmission limit constraint of the interconnected converter, the constraints of the normalized virtual inertia and normalized virtual capacitance are designed. By utilizing fuzzy control, the real-time normalized virtual inertia and normalized virtual capacitance values ​​are obtained according to the dynamic changes of the input variables.

2. The method for virtual inertia fuzzy adaptive control of power fusion station according to claim 1 is characterized in that: The normalized AC frequency and normalized DC voltage are obtained by the following formula: In the formula, ω ac and u dc are the AC bus frequency and DC bus voltage, ω acs and u dcs are the sampling values ​​of AC bus frequency and DC bus voltage respectively, ω a and ω β are the cutoff frequencies of frequency sampling and voltage sampling respectively, s is the differential operator, ω acs.pu and u dcs.pu are the normalized AC frequency and the normalized DC voltage, ω max and ω min The AC frequency ω is ac The corresponding maximum and minimum limit values, u max and u min The DC voltage u dc The corresponding maximum and minimum limits, ω acN and u dcN They are ω ac and u dc Rated value.

3. The method for virtual inertia fuzzy adaptive control of power fusion station according to claim 1, characterized in that: The normalized AC frequency change rate and the normalized DC voltage change rate are obtained by the following formula: Where dω acs / dt and du dcs / dt are the rate of change of AC frequency and DC voltage respectively, and They are respectively expressed as the normalized AC frequency change rate and the normalized DC voltage change rate, (dω ac / dt) limit and dc / dt) limit They are respectively expressed as the limit value of the AC frequency change rate and the limit value of the DC voltage change rate.

4. The method for virtual inertia fuzzy adaptive control of a power fusion station according to claim 1, characterized in that: The active power reference equation is obtained by the following formula: In the formula is the reference value of the active power of the interconnected converter, P ILC is the active power actually output by the interconnected converter, K is the droop coefficient of the double droop control, J v and C v are the normalized virtual inertia and normalized virtual capacitance, ω acs.pu and u dcs.pu are the normalized AC frequency and the normalized DC voltage, respectively, and They are expressed as the normalized AC frequency change rate and the normalized DC voltage change rate respectively.

5. The method for virtual inertia fuzzy adaptive control of a power fusion station according to claim 4, characterized in that: The constraints of normalized virtual inertia and normalized virtual capacitance are obtained by the following formula: Where P ILC.max is the maximum power transmitted by the interconnected converter, J V.max and C V.max are the maximum value of normalized virtual inertia and the maximum value of normalized virtual capacitance, respectively. and They are respectively represented as the normalized values ​​of the limit value of the frequency change rate and the limit value of the voltage change rate, and both of them are 1.

6. The method for virtual inertia fuzzy adaptive control of electric power fusion station according to claim 1, characterized in that: Get real-time normalized virtual inertia and normalized virtual capacitance values, including: Determine the capacity ratio λ between the AC and DC sides; Select and As input variables, the real-time normalized virtual inertia and normalized virtual capacitance values ​​are used as output variables; where, and They are expressed as the normalized AC frequency change rate and the normalized DC voltage change rate respectively; Define fuzzy subsets of input variables and output variables, select membership functions, and set fuzzy rules; The input variables are fuzzified by the fuzzy controller, and then sent to the defuzzification module after reasoning through the fuzzy rule statement. The centroid method is used to defuzzify and obtain the value of the output variable.

7. The method for virtual inertia fuzzy adaptive control of a power fusion station according to claim 6, characterized in that: The ratio of the capacity on both sides of AC and DC, λ, is obtained by the following formula: Where P acN is the rated power of AC measurement, P dcN Rated power measured for DC.

8. The method for virtual inertia fuzzy adaptive control of electric power fusion station according to claim 6, characterized in that: Fuzzy rules are obtained through the following table: Among them, the fuzzy subset of the input variables is {VS, MS, Z, MB, VB}, and the fuzzy subset of the output variables is the same as the fuzzy subset of the input variables; among them, VS, MS, Z, MB, and VB represent "very small", "small", "medium", "large", and "very large", respectively; the membership function is a triangular membership function; the ratio of the variables in the fuzzy subsets of the two input variables is the ratio of the real-time normalized virtual inertia and the normalized virtual capacitance value.

9. The method for virtual inertia fuzzy adaptive control of electric power fusion station according to claim 1, characterized in that: The real-time normalized virtual inertia and normalized virtual capacitance values ​​are obtained by the application and fed back to the inverter control system of the power fusion station.

10. A virtual inertia fuzzy adaptive control system for an electric power fusion station, applying the virtual inertia fuzzy adaptive control method for an electric power fusion station according to any one of claims 1 to 9, comprising: The sampling module is used to sample the AC frequency and the DC voltage, and normalize the sampled values ​​to obtain the normalized AC frequency and the normalized DC voltage; A change rate module is used to obtain the AC frequency change rate and the DC voltage change rate according to the sampled values ​​of the AC frequency and the DC voltage, and then perform normalization processing to obtain the normalized AC frequency change rate and the normalized DC voltage change rate; An active power module is used to construct an active power reference equation according to the actual output power of the interconnector, the normalized AC frequency, the normalized DC voltage, the normalized AC frequency change rate, and the normalized DC voltage change rate; A constraint module is used to design constraints on normalized virtual inertia and normalized virtual capacitance values ​​according to an active power reference equation and in combination with power transmission limit constraints of interconnected converters; The adaptive control module is used to obtain the real-time normalized virtual inertia and normalized virtual capacitance values ​​according to the dynamic changes of input variables by using fuzzy control.

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