A micro-grid frequency stability control method and system considering wind storage cooperation

Abstract

This invention discloses a microgrid frequency stability control method and system considering wind-storage synergy in the field of microgrid control strategy technology. The method includes: introducing a droop control module and constructing a droop response relationship between the actual output power of the wind turbine and the microgrid angular frequency deviation; constructing a steady-state model of the VSG system based on the grid-connected equivalent circuit of the virtual synchronous generator (VSG); introducing the droop response relationship into the VSG system steady-state model and performing small-signal analysis to obtain a wind-storage coupled small-signal system; obtaining the active power output transfer function containing the wind turbine droop response coefficient and the value range of the VSG's virtual inertia and damping coefficient based on the wind-storage coupled small-signal system; setting fuzzy rules based on the value range of the VSG's virtual inertia and damping coefficient, as well as the microgrid frequency deviation and microgrid frequency change rate, constructing a fuzzy logic controller, and using the fuzzy logic controller to adjust the virtual inertia and damping coefficient in the VSG.

Description

Technical Field

[0001] This invention relates to the field of microgrid control strategy technology, and in particular to a microgrid frequency stability control method and system that considers wind and energy storage synergy. Background Technology

[0002] The intermittent and random nature of renewable energy generation, along with the time-varying fluctuations in load, introduces significant uncertainties into the power system, greatly increasing the difficulty of grid planning, operation scheduling, and stability control decisions. Virtual synchronous generator (VSG) technology, by simulating the rotor inertia and damping characteristics of a synchronous generator, can effectively improve the inertia level and frequency support capability of microgrids, and has become an important technical approach for microgrid stability control.

[0003] However, traditional VSGs generally adopt a fixed-parameter control architecture, which has inherent limitations in structural and parameter design, resulting in insufficient adaptability to changes in operating conditions. When the microgrid switches between grid-connected and off-grid modes, experiences sudden load changes, or experiences fluctuations in renewable energy output, the VSG inertia and damping parameters cannot match the dynamic demands of the system in real time. This can easily lead to problems such as severe active power oscillations, large frequency overshoot, and excessively long settling times. In extreme cases, it can even cause frequency overshoot and excessive power surges, threatening the stability of microgrid operation and the continuity of power supply. Furthermore, this control method has poor robustness in multi-source collaborative operation scenarios, easily leading to uneven power distribution and instability in coordinated control, making it difficult to balance dynamic response speed and steady-state control accuracy. These problems not only restrict the safe and stable operation of microgrids under complex conditions but also pose challenges to the planning, construction, and optimized scheduling of grids with a high proportion of renewable energy. Therefore, there is an urgent need to propose improved technical solutions with stronger adaptability and robustness. Summary of the Invention

[0004] The purpose of this invention is to overcome the shortcomings of existing technologies and provide a microgrid frequency stability control method and system that considers wind and energy storage synergy. This method can adaptively change the virtual inertia parameter of the VSG based on the frequency deviation and rate of change at the microgrid's point of common coupling. and damping coefficient Optimizing the power quality of microgrids is of great significance for the planning and construction of microgrids.

[0005] To solve the above-mentioned technical problems, the present invention is implemented using the following technical solution:

[0006] In a first aspect, the present invention provides a microgrid frequency stability control method considering wind and energy storage synergy, comprising:

[0007] A droop control module is introduced into the active power outer loop of the rotor-side converter of the doubly fed wind turbine in the microgrid to construct the droop response relationship between the actual output power of the wind turbine and the angular frequency deviation of the microgrid.

[0008] Based on the grid-connected equivalent circuit of the virtual synchronous generator (VSG), a steady-state model of the VSG system is constructed.

[0009] The droop response relationship is introduced into the rotor motion equation of the VSG system steady-state model, and small-signal analysis is performed on the VSG system steady-state model after the introduction to obtain the wind-storage coupled small-signal system.

[0010] The active power output transfer function, which includes the droop response coefficient of the wind turbine, is obtained from the wind-storage coupled small-signal system.

[0011] Based on the wind-storage coupled small-signal system and the active power output transfer function including the wind turbine droop response coefficient, the range of values ​​for the virtual inertia and damping coefficient of the VSG is obtained.

[0012] Based on the range of values ​​for the virtual inertia and damping coefficient of the VSG, as well as the frequency deviation and frequency change rate of the microgrid, fuzzy rules are set to construct a fuzzy logic controller.

[0013] Based on the real-time microgrid frequency deviation and microgrid frequency change rate, the virtual inertia and damping coefficient in the VSG are adjusted using a fuzzy logic controller.

[0014] Optionally, the relationship between the actual output power of the wind turbine and the droop response of the microgrid angular frequency deviation is shown in the following formula:

[0015] (1),

[0016] (2),

[0017] in, This indicates the additional active power compensation amount for the wind turbine. This represents the sag coefficient of the wind turbine. Indicates the microgrid angular frequency deviation. This indicates the actual output power of the wind turbine. This represents the reference value for comprehensive active power.

[0018] Optionally, the step of constructing a steady-state model of the VSG system based on the grid-connected equivalent circuit of the virtual synchronous generator (VSG) includes:

[0019] Based on the grid-connected equivalent circuit of the virtual synchronous generator (VSG) and Kirchhoff's voltage law, the expression for the output voltage of the VSG is derived as follows:

[0020] (3),

[0021] in, This indicates the output voltage of the VSG. This represents the voltage at the point of common coupling. This indicates the output current of the VSG. This represents the virtual synchronous reactance, and j represents the imaginary unit;

[0022] Based on the expression for the output voltage of the VSG, the expression for the output current of the VSG is obtained as follows:

[0023] (4),

[0024] Substituting the phase angle into the expression for the output current of the VSG, we get:

[0025] (5),

[0026] in, express and The phase difference between them;

[0027] According to formula (5), the expression for the apparent power of the VSG output is as follows:

[0028] (6),

[0029] in, This indicates the apparent power output of the VSG;

[0030] Using Euler's formula to simplify equation (6), we get:

[0031] (7),

[0032] according to By comparing formula (7) By taking the real and imaginary parts of the expression, we obtain the following expression for the active power of the VSG:

[0033] (8),

[0034] in, This indicates the active power of the VSG;

[0035] The expression for the reactive power of VSG is as follows:

[0036] (9),

[0037] in, This indicates the reactive power of the VSG;

[0038] By combining the expressions for active power and reactive power of the VSG, we obtain the steady-state model of the VSG system:

[0039] .

[0040] Optionally, the step of incorporating the droop response relationship into the rotor motion equations of the VSG system steady-state model, and performing small-signal analysis on the VSG system steady-state model after the incorporation to obtain a wind-storage coupled small-signal system includes:

[0041] According to the steady-state model of the VSG system, at the steady-state operating point Linearization of the vicinity yields:

[0042] (10)

[0043] in, This represents the change in power. , To represent partial derivatives, This represents the change in phase angle. ;

[0044] Let the synchronization coefficient ,get The expression is:

[0045] (11),

[0046] Transforming formula (11) into the complex frequency domain, we obtain the following expression:

[0047] (12),

[0048] in, Represents complex variables in the complex plane. This represents the change in power in the complex frequency domain. This represents the change in phase angle in the complex frequency domain;

[0049] The expression for the relationship between angular velocity and power angle in VSG is as follows:

[0050] (13)

[0051] in, Indicates the actual angular velocity. Indicates the initial angular velocity;

[0052] Linearizing equation (13), we get:

[0053] (14)

[0054] in, Indicates the microgrid angular frequency deviation;

[0055] The expression for the rotor motion equation of VSG is as follows:

[0056] (15)

[0057] in, This indicates the mechanical power of the VSG. This indicates the electromagnetic power of the VSG. Indicates the damping coefficient. Represents virtual inertia;

[0058] Introducing the droop response relationship into formula (15) and linearizing it, we obtain the linearized equation for wind-storage coupling:

[0059] (16)

[0060] in, This represents the change in the mechanical power of the VSG. This indicates the change in the electromagnetic power of the VSG;

[0061] Combining equations (11), (14), and (16), we obtain the wind-storage coupled small-signal system:

[0062] .

[0063] Optionally, obtaining the active power output transfer function including the wind turbine droop response coefficient based on the wind-storage coupled small-signal system includes:

[0064] Taking the Laplace transform of equation (13) yields:

[0065] (17)

[0066] in, Represents the angular velocity in the complex frequency domain;

[0067] Taking the Laplace transform of equation (15) yields:

[0068] (18)

[0069] Combining equations (12), (17), and (18), we get:

[0070] (19)

[0071] According to formula (19), the active power output transfer function including the droop response coefficient of the wind turbine is obtained as follows:

[0072] (20)

[0073] in, This represents the active power output transfer function that includes the sag response coefficient of the wind turbine.

[0074] Optionally, the step of obtaining the range of values ​​for the virtual inertia and damping coefficient of the VSG based on the wind-storage coupled small-signal system and the active power output transfer function including the wind turbine droop response coefficient includes:

[0075] Treating the wind-storage coupled small-signal system as a standard second-order system, its key indicators include the oscillation frequency of the VSG. Peak time 2% steady-state time and overshoot ;

[0076] According to the oscillation frequency of the VSG Peak time 2% steady-state time and overshoot Damping ratio with VSG and natural oscillation angular frequency The relationship between the two factors yields the damping ratio. The optimal range of values ​​is Natural oscillation angular frequency The optimal range of values ​​is ;

[0077] According to the damping ratio The optimal range of values ​​and natural oscillation angular frequency The optimal range of values ​​and the damping ratio Natural oscillation angular frequency Virtual inertia Damping coefficient and wind turbine sag coefficient The relationship is used to obtain the virtual inertia. The per-unit value range is Virtual inertia The actual range of values ​​is Damping coefficient The per-unit value range is Damping coefficient The actual range of values ​​is ;

[0078] The damping ratio The expression is:

[0079] (twenty one),

[0080] in, Indicates the synchronization coefficient;

[0081] The natural oscillation angular frequency The expression is:

[0082] (twenty two),

[0083] The oscillation frequency of the VSG The expression is:

[0084] (twenty three),

[0085] The peak time The expression is:

[0086] (twenty four),

[0087] The 2% steady-state time The expression is:

[0088] (25),

[0089] The overshoot The expression is:

[0090] (26)

[0091] in, This represents the natural exponential function.

[0092] Optionally, the step of setting fuzzy rules based on the range of values ​​for the virtual inertia and damping coefficient of the VSG, as well as the microgrid frequency deviation and microgrid frequency change rate, and constructing a fuzzy logic controller includes:

[0093] The microgrid frequency deviation and microgrid frequency change rate are divided into five input language values, including negative large NB, negative small NS, zero Z, positive small PS and positive large PB;

[0094] virtual inertia and damping coefficient It is divided into five output language values, including minimal VS, minor S, medium M, large L and maximum VL;

[0095] Based on the coordinated droop response of wind turbines, the larger the frequency change rate of the microgrid, the greater the virtual inertia. Based on the principle that the larger the frequency deviation, the greater the total equivalent damping required by the system, a virtual inertia is set. and damping coefficient Fuzzy rules;

[0096] Based on virtual inertia and damping coefficient The fuzzy rules, with microgrid frequency deviation and microgrid frequency change rate as inputs, and virtual inertia. and damping coefficient To generate the output, construct a fuzzy logic controller; Figure 7 This is a schematic diagram of a fuzzy adaptive parameter tuning controller for VSG control. The controller uses the microgrid frequency deviation... With microgrid frequency change rate It is a dual-input feedback quantity, which is fed through input quantization factors. The fuzzy input is obtained after performing a universe transformation. The input is fed into the fuzzy inference module; the fuzzy module generates the corresponding fuzzy output through fuzzification, fuzzy rule base inference, and defuzzification, and then outputs the quantization factor. Perform an inverse scaling transformation to finally output the virtual inertia change of the VSG system. and the change in damping coefficient ;in, This represents the initial value of the virtual inertia. This represents the initial value of the damping coefficient. The control structure realizes adaptive tuning of key VSG parameters based on the dynamic state of the frequency. It can optimize the virtual inertia and damping parameters in real time under conditions such as sudden load increase and grid connection / off-grid switching, effectively suppressing large frequency oscillations and overshoot, and improving the frequency stability and robustness of the microgrid under disturbances with a high proportion of new energy sources.

[0097] The virtual inertia The fuzzy rules are as follows:

[0098] If the frequency deviation is NB and the frequency change rate is NB, then Let VL be the frequency deviation; if the frequency deviation is NB and the frequency change rate is NS, then... Let L be the frequency deviation; if the frequency deviation is NB and the frequency change rate is Z, then... Let L be the frequency deviation; if the frequency deviation is NB and the frequency change rate is PS, then Let M be the frequency deviation; if the frequency deviation is NB and the frequency change rate is PB, then... For M;

[0099] If the frequency deviation is NS and the frequency change rate is NB, then Let L be the frequency deviation; if the frequency deviation is N / S and the frequency change rate is N / S, then Let L be the frequency deviation; if the frequency deviation is N / S and the frequency change rate is Z, then Let M be the frequency deviation; if the frequency deviation is N / S and the frequency change rate is PS, then... Let M be the frequency deviation; if the frequency deviation is NS and the frequency change rate is PB, then... S;

[0100] If the frequency deviation is Z and the frequency change rate is NB, then Let L be the frequency deviation; if the frequency deviation is Z and the frequency change rate is NS, then Let M be the frequency deviation; if the frequency deviation is Z and the frequency change rate is Z, then... Let VS be the frequency deviation; if the frequency deviation is Z and the frequency change rate is PS, then Let M be the frequency deviation; if the frequency deviation is Z and the frequency change rate is PB, then... Let L be the value.

[0101] If the frequency deviation is PS and the frequency change rate is NB, then Let M be the frequency deviation; if the frequency deviation is PS and the frequency change rate is NS, then... Let M be the frequency deviation; if the frequency deviation is PS and the frequency change rate is Z, then... Let M be the frequency deviation; if the frequency deviation is PS and the frequency change rate is PS, then Let L be the frequency deviation; if the frequency deviation is PS and the frequency change rate is PB, then Let L be the value.

[0102] If the frequency deviation is PB and the frequency change rate is NB, then Let M be the frequency deviation; if the frequency deviation is PB and the frequency change rate is NS, then... Let S be the frequency deviation; if the frequency deviation is PB and the frequency change rate is Z, then... Let L be the frequency deviation; if the frequency deviation is PB and the frequency change rate is PS, then Let L be the frequency deviation; if the frequency deviation is PB and the frequency change rate is PB, then VL;

[0103] The damping coefficient The fuzzy rules are as follows:

[0104] If the frequency deviation is NB and the frequency change rate is NB, then Let VL be the frequency deviation; if the frequency deviation is NB and the frequency change rate is NS, then... Let L be the frequency deviation; if the frequency deviation is NB and the frequency change rate is Z, then... Let L be the frequency deviation; if the frequency deviation is NB and the frequency change rate is PS, then Let M be the frequency deviation; if the frequency deviation is NB and the frequency change rate is PB, then... S;

[0105] If the frequency deviation is NS and the frequency change rate is NB, then Let L be the frequency deviation; if the frequency deviation is N / S and the frequency change rate is N / S, then Let M be the frequency deviation; if the frequency deviation is N / S and the frequency change rate is Z, then... Let M be the frequency deviation; if the frequency deviation is N / S and the frequency change rate is PS, then... Let S be the frequency deviation; if the frequency deviation is N / S and the frequency change rate is PB, then... For VS;

[0106] If the frequency deviation is Z and the frequency change rate is NB, then Let L be the frequency deviation; if the frequency deviation is Z and the frequency change rate is NS, then Let M be the frequency deviation; if the frequency deviation is Z and the frequency change rate is Z, then... Let M be the frequency deviation; if the frequency deviation is Z and the frequency change rate is PS, then... Let M be the frequency deviation; if the frequency deviation is Z and the frequency change rate is PB, then... Let L be the value.

[0107] If the frequency deviation is PS and the frequency change rate is NB, then Let VS be the frequency deviation; if the frequency deviation is PS and the frequency change rate is NS, then Let S be the frequency deviation; if the frequency deviation is PS and the frequency change rate is Z, then... Let M be the frequency deviation; if the frequency deviation is PS and the frequency change rate is PS, then Let M be the frequency deviation; if the frequency deviation is PS and the frequency change rate is PB, then... Let L be the value.

[0108] If the frequency deviation is PB and the frequency change rate is NB, then Let S be the frequency deviation; if the frequency deviation is PB and the frequency change rate is NS, then... Let M be the frequency deviation; if the frequency deviation is PB and the frequency change rate is Z, then... Let L be the frequency deviation; if the frequency deviation is PB and the frequency change rate is PS, then Let L be the frequency deviation; if the frequency deviation is PB and the frequency change rate is PB, then VL.

[0109] In a second aspect, the present invention provides a computer-readable storage medium having computer instructions stored thereon, which, when executed by a processor, implement the steps of any of the microgrid frequency stability control methods considering wind and energy storage synergy described in the first aspect.

[0110] Thirdly, the present invention provides a computer program product, including computer instructions that, when executed by a processor, implement the steps of the microgrid frequency stability control method considering wind and energy storage synergy as described in any of the first aspects.

[0111] Fourthly, the present invention provides a computer program product, including computer instructions, characterized in that, when the computer instructions are executed by a processor, they implement the steps of the microgrid frequency stability control method considering wind and energy storage synergy as described in any of the first aspects.

[0112] Compared with the prior art, the beneficial effects achieved by the present invention are as follows:

[0113] 1. Based on the frequency deviation and rate of change at the microgrid's point of common coupling, the virtual inertia and damping coefficient of the VSG can be adaptively changed to optimize the power quality of the microgrid; it can assist in the formulation of various decisions during microgrid planning and operation, thereby reducing potential safety and economic risks, and further supporting applications such as microgrid operation and control, dynamic source-load planning, and improving the absorption capacity of new energy sources.

[0114] 2. The microgrid control strategy improves upon the traditional microgrid scenario where frequency regulation only considers a single energy storage unit. This scenario often includes only a limited number of modules and cannot fully represent the problems in microgrid operation. The microgrid frequency stability control strategy, which considers wind-storage synergy and is generated based on wind-solar-storage microgrids, can effectively reflect the fluctuations caused by the switching of operating conditions in actual operation of the microgrid. It also effectively reduces the deviation of system frequency during the switching of operating conditions, optimizes the power quality of the system, and further supports applications such as microgrid operation regulation, dynamic source-load planning, and improving the absorption capacity of new energy sources. Attached Figure Description

[0115] Figure 1 This is a flowchart of a microgrid frequency stability control method considering wind and energy storage synergy according to an embodiment of the present invention.

[0116] Figure 2 This is a schematic diagram of an improved rotor-side converter control for a wind power module according to an embodiment of the present invention.

[0117] Figure 3 A root locus diagram of a VSG provided according to an embodiment of the present invention;

[0118] Figure 4 This is a typical frequency response curve of a VSG under a unit step disturbance according to an embodiment of the present invention.

[0119] Figure 5 The VSG provided according to the embodiments of the present invention is in and A diagram showing the phase margin variation when both phases change together.

[0120] Figure 6 The diagram shows the power angle characteristics, frequency deviation, and frequency change rate curves of a microgrid system under sudden load increase according to an embodiment of the present invention.

[0121] Figure 7 This is a schematic diagram of a fuzzy adaptive parameter tuning controller structure for VSG control provided in an embodiment of the present invention;

[0122] Figure 8 This is a dynamic variation curve of the output power of a microgrid system over time under different control conditions according to an embodiment of the present invention;

[0123] Figure 9 This is a graph showing the dynamic change of frequency over time in a microgrid system under different control conditions according to an embodiment of the present invention. Detailed Implementation

[0124] The technical solution of the present invention will be described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the embodiments and specific features in the embodiments are detailed descriptions of the technical solution of the present application, rather than limitations thereof. In the absence of conflict, the embodiments and technical features in the embodiments can be combined with each other.

[0125] It should be noted that the term "and / or" in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, the character " / " in this article generally indicates that the preceding and following related objects have an "or" relationship.

[0126] Example 1:

[0127] This invention discloses a microgrid frequency stability control method considering wind and energy storage synergy, with reference to... Figure 1 As shown, the specific steps include the following:

[0128] S1. A droop control module is introduced into the active power outer loop of the rotor-side converter of the doubly fed wind turbine in the microgrid to construct the droop response relationship between the actual output power of the wind turbine and the angular frequency deviation of the microgrid.

[0129] S2. Construct a steady-state model of the VSG system based on the grid-connected equivalent circuit of the virtual synchronous generator VSG;

[0130] S3, The droop response relationship is introduced into the rotor motion equation of the VSG system steady-state model, and small-signal analysis is performed on the VSG system steady-state model after the introduction to obtain the wind-storage coupled small-signal system;

[0131] S4, Obtain the active power output transfer function including the droop response coefficient of the wind turbine unit based on the wind-storage coupled small signal system;

[0132] S5. Based on the wind-storage coupled small-signal system and the active power output transfer function including the wind turbine droop response coefficient, the range of values ​​for the virtual inertia and damping coefficient of the VSG is obtained.

[0133] S6. Based on the range of values ​​of the virtual inertia and damping coefficient of VSG, as well as the frequency deviation and frequency change rate of the microgrid, fuzzy rules are set to construct a fuzzy logic controller.

[0134] S7, based on the real-time microgrid frequency deviation and microgrid frequency change rate, uses a fuzzy logic controller to adjust the virtual inertia and damping coefficient in the VSG.

[0135] Specifically, in step S1, the rotor-side converter and grid-side converter of the doubly-fed induction generator used in the wind turbine adopt power-current dual-loop control and voltage-current dual-loop control, respectively; the grid-side converter mainly maintains the constant DC bus voltage of the unit and controls the reactive power exchanged between the grid-side converter and the grid; the rotor-side converter is used to precisely control the active and reactive power output of the stator side of the doubly-fed induction generator.

[0136] To enable wind turbines to have frequency regulation capabilities, an active-frequency droop control module is added to the active power outer loop of the rotor-side converter to achieve frequency regulation participation; the improved active power outer loop is as follows: Figure 2 As shown, the input mechanical angular velocity of the motor A comprehensive active power reference value is generated through the power tracking module. Then through the torque conversion stage Transform into torque reference value Finally, it goes through the current conversion stage. Output active current reference value ,in This refers to the rotor's d-axis voltage. To give the wind turbine active frequency regulation capability, an active-frequency droop control module is added to the existing active power outer loop: this module uses the system frequency deviation... As input, the droop coefficient of the wind turbine unit Generate additional active power compensation for wind turbine units and the output of the original power tracking module By superimposing the values, the actual output power of the wind turbine can be obtained. .

[0137] The relationship between the actual output power of the wind turbine and the droop response of the microgrid angular frequency deviation is shown in the following formula:

[0138] (1),

[0139] (2),

[0140] in, This indicates the additional active power compensation amount for the wind turbine. This represents the sag coefficient of the wind turbine. Indicates the microgrid angular frequency deviation. This indicates the actual output power of the wind turbine. This represents the reference value for comprehensive active power.

[0141] In step S2, a steady-state model of the VSG system is constructed based on the grid-connected equivalent circuit of the virtual synchronous generator (VSG), including:

[0142] Based on the grid-connected equivalent circuit of the virtual synchronous generator (VSG) and Kirchhoff's voltage law, the expression for the output voltage of the VSG is derived as follows:

[0143] (3),

[0144] in, This indicates the output voltage of the VSG. This represents the voltage at the point of common coupling. This indicates the output current of the VSG. This represents the virtual synchronous reactance, and j represents the imaginary unit;

[0145] Based on the expression for the output voltage of the VSG, the expression for the output current of the VSG is obtained as follows:

[0146] (4),

[0147] Substituting the phase angle into the expression for the output current of the VSG, we get:

[0148] (5),

[0149] in, express and The phase difference between them;

[0150] According to formula (5), the expression for the apparent power of the VSG output is as follows:

[0151] (6),

[0152] in, This indicates the apparent power output of the VSG;

[0153] Using Euler's formula to simplify equation (6), we get:

[0154] (7),

[0155] according to By comparing formula (7) By taking the real and imaginary parts of the expression, we obtain the following expression for the active power of the VSG:

[0156] (8),

[0157] in, This indicates the active power of the VSG;

[0158] The expression for the reactive power of VSG is as follows:

[0159] (9),

[0160] in, This indicates the reactive power of the VSG;

[0161] By combining the expressions for active power and reactive power of the VSG, we obtain the steady-state model of the VSG system:

[0162] .

[0163] In step S3, the change in active power of the wind turbine generated by the droop response relationship is used as an active power support term and introduced into the rotor motion equation of the VSG system steady-state model. Small-signal analysis is then performed on the resulting steady-state model to obtain a wind-storage coupled small-signal system considering the damping support of the wind turbine, including:

[0164] According to the steady-state model of the VSG system, at the steady-state operating point Linearization of the vicinity yields:

[0165] (10)

[0166] in, This represents the change in power. , To represent partial derivatives, This represents the change in phase angle. ;

[0167] Let the synchronization coefficient ,get The expression is:

[0168] (11),

[0169] Transforming formula (11) into the complex frequency domain, we obtain the following expression:

[0170] (12),

[0171] in, Represents complex variables in the complex plane. This represents the change in power in the complex frequency domain. This represents the change in phase angle in the complex frequency domain;

[0172] The expression for the relationship between angular velocity and power angle in VSG is as follows:

[0173] (13)

[0174] in, Indicates the actual angular velocity. Indicates the initial angular velocity;

[0175] Linearizing equation (13), we get:

[0176] (14)

[0177] in, Indicates the microgrid angular frequency deviation;

[0178] The expression for the rotor motion equation of VSG is as follows:

[0179] (15)

[0180] in, This indicates the mechanical power of the VSG. This indicates the electromagnetic power of the VSG. Indicates the damping coefficient. Represents virtual inertia;

[0181] Because active power-frequency droop control is introduced on the rotor side of the wind turbine, the wind turbine will output additional active power compensation when the system frequency fluctuates. Therefore, by taking the wind turbine support power as the equivalent mechanical power input and linearizing equation (15), we obtain the linearized equation for wind-storage coupling:

[0182] (16)

[0183] in, This represents the change in the mechanical power of the VSG. This indicates the change in the electromagnetic power of the VSG;

[0184] Combining equations (11), (14), and (16), we obtain the wind-storage coupled small-signal system:

[0185] .

[0186] In step S4, the active power output transfer function, including the wind turbine droop response coefficient, is obtained based on the wind-storage coupled small-signal system, including:

[0187] Taking the Laplace transform of equation (13) yields:

[0188] (17)

[0189] in, Represents the angular velocity in the complex frequency domain;

[0190] Taking the Laplace transform of equation (15) yields:

[0191] (18)

[0192] Combining equations (12), (17), and (18), we get:

[0193] (19)

[0194] According to formula (19), the active power output transfer function including the droop response coefficient of the wind turbine is obtained as follows:

[0195] (20)

[0196] in, This represents the active power output transfer function that includes the sag response coefficient of the wind turbine.

[0197] In step S5, Figure 3 To fix virtual inertia separately and fixed damping coefficient The root locus plot of the VSG under the following conditions; data1 represents the imaginary axis, which is the boundary line of VSG stability, and data2 represents the real axis, which is the boundary line of VSG oscillation / non-oscillation; within a large range, and The values ​​of all values ​​can keep the VSG stable; a fixed damping coefficient In the case of, When the value is small, the poles are far from the imaginary axis, the imaginary part is large, the VSG response is fast but the damping is insufficient. As the inertia increases, the poles gradually approach the real axis, the VSG's response speed decreases, but its stability improves; with a fixed virtual inertia... In the case of, When the value is small, the poles are close to the imaginary axis, and the system oscillates strongly. As the value increases... As the damping ratio increases, the poles move along the line of constant damping ratio and eventually separate on the real axis, one tending towards the origin and the other towards negative infinity. The process of increasing damping is also the process of VSG transitioning from underdamped to critically damped, and finally reaching overdamped.

[0198] The performance of the VSG under disturbances is analyzed using the unit step response diagram. Figure 4 It can be seen that when virtual inertia and damping coefficient The typical frequency response curve of VSG under a unit step disturbance changes when the damping coefficient changes; =2, increasing virtual inertia alone At that time, the rise time and peak time of VSG increased significantly because as The increase of VSG's natural oscillation angular frequency As the voltage decreases, the overall response of the VSG slows down, requiring a longer time to respond and reach peak performance. Simultaneously, the VSG's settling time also increases. Furthermore, with... As the damping ratio of the VSG increases, the overshoot of the VSG will also increase, due to the increased damping ratio of the VSG. Follow The reduction is caused by the decrease; fixed virtual inertia =2, at the damping coefficient As damping increases, the rise time and peak time of the VSG increase because with stronger damping, the VSG response becomes more viscous, slowing down the rate at which the setpoint or peak value is reached. Simultaneously, the VSG's settling time initially decreases and then changes more gradually because this occurs in the underdamped region, i.e. When the damping coefficient is small, increasing it can quickly quell oscillations and significantly shorten the settling time. However, when the damping coefficient increases to near the critical damping, the change in settling time decreases. Furthermore, because of the damping ratio... The direct increase of VSG can more effectively suppress oscillations, thus significantly reducing the overshoot of VSG.

[0199] VSGs require sufficient phase margin during operation, which in practical engineering typically needs to be greater than 30°. To ensure this, the system needs to be analyzed using a phase margin diagram, such as... Figure 5 As shown, it can be seen that and When the phase angle is relatively small, although the VSG has a relatively sufficient phase margin, its ability to resist external disturbances is weak; and When the phase margin is larger, the phase margin is more sufficient, but the system response speed will be slower. Larger and When the value is small, the large virtual inertia pulls the phase lag region to a low frequency, while the small damping coefficient pushes the system's amplitude crossover frequency to this region with severe phase lag. Therefore, the phase margin of the VSG is low.

[0200] Figure 6 Using the power angle, frequency, and rate of change of the microgrid system during a load surge as references, this paper comprehensively demonstrates the dynamic response of a VSG-based microgrid system under load surge conditions from three dimensions: power angle characteristics, frequency deviation, and rate of change of frequency. The physical meanings of each sub-figure are as follows: Sub-figure (a) shows the power angle characteristic curve of the microgrid system, following the synchronous generator... The power angle characteristic is shown, where the blue dashed line represents the mechanical power before the load surge, and the red dashed line represents the mechanical power after the load surge. The following parameters are also indicated. The power angle and power state at four key characteristic points; sub-figure (b) shows the time-domain curve of the frequency difference in the microgrid system, intuitively reflecting the amplitude and oscillation process of the frequency deviation from the rated value; sub-figure (c) shows the time-domain curve of the frequency change rate of the microgrid system, characterizing the speed of dynamic frequency change. To clearly explain the dynamic change law of the microgrid system, the response process can be divided into a dynamic process with 5 characteristic stages as a complete cycle:

[0201] F1: First stage, i.e., the initial stage :

[0202] At the instant the disturbance begins, the power angle has not yet changed due to rotor inertia, and the frequency begins to decrease, with the rate of change of frequency becoming sharply negative and having a large absolute value. This is because the sudden increase in load causes the electromagnetic power to exceed the mechanical power, causing the rotor to begin decelerating. At this time, the virtual inertia... It should be reduced immediately because a large virtual inertia will hinder the system's rapid detection and response to disturbances. This allows frequency deviations to be reflected in power angle changes more quickly, enabling the VSG to activate earlier; simultaneously, the damping coefficient... It should be increased immediately to provide strong initial damping and suppress the sharp drop in frequency.

[0203] F2: The second stage, namely the acceleration and deceleration stage. :

[0204] During this stage, the power angle increases, the frequency continues to decrease, and the rate of frequency change remains negative, but its absolute value decreases. This is a stage where the rotor continuously decelerates, converting kinetic energy into electromagnetic energy. At this time, the virtual inertia... A small value should be maintained for the VSG to respond quickly; damping coefficient It should be kept relatively large to continue suppressing the frequency decrease.

[0205] F3: The third stage, in which the maximum power angle is reached. :

[0206] During this phase, the power angle reaches its peak, and the frequency reaches its lowest point with a rate of change of zero, marking the transition from negative to positive. At this time, deceleration stops, acceleration power is zero, and virtual inertia... The damping coefficient should be increased initially to allow sufficient inertial transition for the VSG and prevent VSG overshoot; It should be kept very large because the VSG is extremely vulnerable at this point and requires high damping to maintain its stability.

[0207] F4: The fourth stage, namely the recovery and acceleration stage. :

[0208] During this stage, the power angle begins to decrease, the frequency begins to rise, and the rate of frequency change becomes positive. At this point, the VSG generates additional mechanical power, and the rotor begins to accelerate. Virtual inertia. The damping coefficient should be appropriately increased to provide stability and prevent excessive system oscillation. The damping should be reduced to avoid overdamping that hinders frequency recovery.

[0209] F5: The fifth stage, namely the swing back stage:

[0210] During this phase, the power angle exceeds the initial power angle and swings in the opposite direction. The frequency may exceed the rated value, and the rate of change of frequency changes from positive to negative again. At this point, the VSG has excess kinetic energy and begins to decelerate; the virtual inertia should be appropriately reduced. And further increase the damping coefficient To suppress reverse oscillations.

[0211] Therefore, this embodiment treats the VSG small-signal system as a standard second-order system, whose key indicators include the oscillation frequency of the VSG. Peak time 2% steady-state time and overshoot :

[0212] The damping ratio The expression is:

[0213] (twenty one),

[0214] in, Indicates the synchronization coefficient;

[0215] The natural oscillation angular frequency The expression is:

[0216] (twenty two),

[0217] The oscillation frequency of the VSG The expression is:

[0218] (twenty three),

[0219] The peak time The expression is:

[0220] (twenty four),

[0221] The 2% steady-state time The expression is:

[0222] (25),

[0223] The overshoot The expression is:

[0224] (26)

[0225] in, This represents the natural exponential function.

[0226] when When VSG is in an unstable or critically stable state, its use in actual VSG is prohibited; when At that time, the VSG is in a lightly damped state. Oscillation frequency. Overshoot More than 30% of its steady-state change, steady-state time Long-term operation poses a higher risk to weak grids, such as microgrids; when At this time, the VSG still has a large oscillation frequency and overshoot. It is approximately 10%-30% of its steady-state variation, and the steady-state time is short, making it unsuitable for microgrids; when When the VSG's overshoot is less than 10% of its steady-state change, its steady-state time is moderate, and its robustness is good; when At this time, the VSG is in a critical damping state; although the overshoot is small, the required damping power is large, and it is more sensitive to measurement noise and limiting; when At this time, the VSG is in an overdamped state. Although the overshoot is small, the VSG response time is slow, which is not suitable for VSGs with high uncertainty in microgrids.

[0227] when At speeds < 6 rad / s, the VSG response is slow, exhibiting good noise immunity but not being suitable for rapid support; when... At 12–30 rad / s: velocity and robustness are balanced; when At 12–30 rad / s: the response speed is fast, but it requires higher voltage / current inner loop bandwidth and sampling delay margin, and measurement noise and quantization error are more easily amplified.

[0228] Based on the above derivation and the oscillation frequency of the VSG, Peak time 2% steady-state time and overshoot Damping ratio with VSG Natural oscillation angular frequency Virtual inertia and damping coefficient and wind turbine sag coefficient The relationship between damping ratio in microgrids with a high proportion of renewable energy The value should be selected between 0.4 and 0.8, representing the natural oscillation angular frequency. Taken at 6–12 rad / s; It is 0.2. Steady-state work angle Furthermore, in a system with an actual capacity of 1 MVA, the virtual inertia is obtained by applying equations (19) and (20). The per-unit value range is Virtual inertia The actual range of values ​​is Damping coefficient The per-unit value range is Damping coefficient The actual range of values ​​is .

[0229] In step S6, the step of setting fuzzy logic based on the range of values ​​for virtual inertia and damping coefficient in the VSG, as well as the microgrid frequency deviation and microgrid frequency change rate, and constructing a fuzzy logic controller includes:

[0230] The microgrid frequency deviation and microgrid frequency change rate are divided into five input language values, including negative large NB, negative small NS, zero Z, positive small PS and positive large PB;

[0231] virtual inertia and damping coefficient It is divided into five output language values, including minimal VS, minor S, medium M, large L and maximum VL;

[0232] Based on the coordinated droop response of wind turbines, the larger the frequency change rate of the microgrid, the greater the virtual inertia. Based on the principle that the larger the frequency deviation, the greater the total equivalent damping required by the system, a virtual inertia is set. and damping coefficient Fuzzy rules;

[0233] Based on virtual inertia and damping coefficient The fuzzy rules, with microgrid frequency deviation and microgrid frequency change rate as inputs, and virtual inertia. and damping coefficient To generate the output, construct a fuzzy logic controller; Figure 6 This is a schematic diagram of a fuzzy adaptive parameter tuning controller for VSG control. The controller uses the microgrid frequency deviation... With microgrid frequency change rate It is a dual-input feedback quantity, which is fed through input quantization factors. The fuzzy input is obtained after performing a universe transformation. The input is fed into the fuzzy inference module; the fuzzy module generates the corresponding fuzzy output through fuzzification, fuzzy rule base inference, and defuzzification, and then outputs the quantization factor. Perform an inverse scaling transformation to finally output the virtual inertia change of the VSG system. and the change in damping coefficient ;in, This represents the initial value of the virtual inertia. This represents the initial value of the damping coefficient. The control structure realizes adaptive tuning of key VSG parameters based on the dynamic state of the frequency. It can optimize the virtual inertia and damping parameters in real time under conditions such as sudden load increase and grid connection / off-grid switching, effectively suppressing large frequency oscillations and overshoot, and improving the frequency stability and robustness of the microgrid under disturbances with a high proportion of new energy sources.

[0234] The virtual inertia The fuzzy rules are as follows:

[0235] If the frequency deviation is NB and the frequency change rate is NB, then Let VL be the frequency deviation; if the frequency deviation is NB and the frequency change rate is NS, then... Let L be the frequency deviation; if the frequency deviation is NB and the frequency change rate is Z, then... Let L be the frequency deviation; if the frequency deviation is NB and the frequency change rate is PS, then Let M be the frequency deviation; if the frequency deviation is NB and the frequency change rate is PB, then... For M;

[0236] If the frequency deviation is NS and the frequency change rate is NB, then Let L be the frequency deviation; if the frequency deviation is N / S and the frequency change rate is N / S, then Let L be the frequency deviation; if the frequency deviation is N / S and the frequency change rate is Z, then Let M be the frequency deviation; if the frequency deviation is N / S and the frequency change rate is PS, then... Let M be the frequency deviation; if the frequency deviation is NS and the frequency change rate is PB, then... S;

[0237] If the frequency deviation is Z and the frequency change rate is NB, then Let L be the frequency deviation; if the frequency deviation is Z and the frequency change rate is NS, then Let M be the frequency deviation; if the frequency deviation is Z and the frequency change rate is Z, then... Let VS be the frequency deviation; if the frequency deviation is Z and the frequency change rate is PS, then Let M be the frequency deviation; if the frequency deviation is Z and the frequency change rate is PB, then... Let L be the value.

[0238] If the frequency deviation is PS and the frequency change rate is NB, then Let M be the frequency deviation; if the frequency deviation is PS and the frequency change rate is NS, then... Let M be the frequency deviation; if the frequency deviation is PS and the frequency change rate is Z, then... Let M be the frequency deviation; if the frequency deviation is PS and the frequency change rate is PS, then Let L be the frequency deviation; if the frequency deviation is PS and the frequency change rate is PB, then Let L be the value.

[0239] If the frequency deviation is PB and the frequency change rate is NB, then Let M be the frequency deviation; if the frequency deviation is PB and the frequency change rate is NS, then... Let S be the frequency deviation; if the frequency deviation is PB and the frequency change rate is Z, then... Let L be the frequency deviation; if the frequency deviation is PB and the frequency change rate is PS, then Let L be the frequency deviation; if the frequency deviation is PB and the frequency change rate is PB, then VL;

[0240] The damping coefficient The fuzzy rules are as follows:

[0241] If the frequency deviation is NB and the frequency change rate is NB, then Let VL be the frequency deviation; if the frequency deviation is NB and the frequency change rate is NS, then... Let L be the frequency deviation; if the frequency deviation is NB and the frequency change rate is Z, then... Let L be the frequency deviation; if the frequency deviation is NB and the frequency change rate is PS, then Let M be the frequency deviation; if the frequency deviation is NB and the frequency change rate is PB, then... S;

[0242] If the frequency deviation is NS and the frequency change rate is NB, then Let L be the frequency deviation; if the frequency deviation is N / S and the frequency change rate is N / S, then Let M be the frequency deviation; if the frequency deviation is N / S and the frequency change rate is Z, then... Let M be the frequency deviation; if the frequency deviation is N / S and the frequency change rate is PS, then... Let S be the frequency deviation; if the frequency deviation is N / S and the frequency change rate is PB, then... For VS;

[0243] If the frequency deviation is Z and the frequency change rate is NB, then Let L be the frequency deviation; if the frequency deviation is Z and the frequency change rate is NS, then Let M be the frequency deviation; if the frequency deviation is Z and the frequency change rate is Z, then... Let M be the frequency deviation; if the frequency deviation is Z and the frequency change rate is PS, then... Let M be the frequency deviation; if the frequency deviation is Z and the frequency change rate is PB, then... Let L be the value.

[0244] If the frequency deviation is PS and the frequency change rate is NB, then Let VS be the frequency deviation; if the frequency deviation is PS and the frequency change rate is NS, then Let S be the frequency deviation; if the frequency deviation is PS and the frequency change rate is Z, then... Let M be the frequency deviation; if the frequency deviation is PS and the frequency change rate is PS, then Let M be the frequency deviation; if the frequency deviation is PS and the frequency change rate is PB, then... Let L be the value.

[0245] If the frequency deviation is PB and the frequency change rate is NB, then Let S be the frequency deviation; if the frequency deviation is PB and the frequency change rate is NS, then... Let M be the frequency deviation; if the frequency deviation is PB and the frequency change rate is Z, then... Let L be the frequency deviation; if the frequency deviation is PB and the frequency change rate is PS, then Let L be the frequency deviation; if the frequency deviation is PB and the frequency change rate is PB, then VL.

[0246] When the load within a microgrid changes, the system power may experience a deficit or surplus, leading to frequency deviation. At this point, the VSG control loop will immediately detect the frequency deviation. and frequency change rate And optimize the damping coefficient according to the preset fuzzy rules. and virtual inertia This immediately prevented the frequency drop; simultaneously, the wind power module also detected the frequency deviation. The power output is adjusted according to equation (25) to provide power support. In this way, the changes in system power will be shared by both energy storage and wind power. Energy storage provides fast, accurate, and bidirectional adjustable power, mainly used to compensate for high-frequency, severe power fluctuations and most of the initial deficit. Wind power provides relatively slow but continuous power support, sharing part of the power deficit, thereby reducing the output burden and energy throughput requirements of energy storage. This allows energy storage to focus on dealing with higher frequency fluctuations, extending the life of energy storage, and also reducing the configuration requirements for the rated power and capacity of the energy storage system.

[0247] This embodiment constructs a microgrid scenario composed of wind power, photovoltaics, energy storage, and loads for simulation. To intuitively analyze the frequency fluctuation characteristics of the microgrid under conditions such as grid-connected / islanded mode switching, sudden changes in renewable energy output, and load switching, the following simulation scenario and operating conditions are set: The total simulation duration is 4 seconds. Initially, the wind power output is 0.5MW, the photovoltaic output is 0.75MW, and the total active load of the microgrid is 1.3MW. The system initially operates stably in grid-connected mode, and each power generation unit outputs power according to the given reference value. At 0.5 seconds, the microgrid performs grid-connected / off-grid switching and enters islanded operation mode. At 1.5 seconds, load switching occurs, and the total active load drops to 1MW. At 2.5 seconds, the solar irradiance fluctuates, and the active power output of the photovoltaic system drops to 0.4MW. The proposed microgrid frequency stability control method considering wind and energy storage synergy was used for simulation verification. To quantitatively compare the effectiveness of different control strategies, three frequency quality inspection indicators were calculated for traditional droop control, VSG control, VSG control with wind power introduction, improved VSG control, and improved VSG control with wind power introduction. The comparison results are shown in Table 1. Among them, the improved VSG control is the VSG control optimized using fuzzy control, and the improved VSG control with wind power introduction is the microgrid frequency stability control method considering wind and energy storage synergy proposed in this embodiment.

[0248] Table 1 Comparison of Clustering Results

[0249] highest frequency Minimum frequency Average frequency deviation Traditional sagging control 50.190HZ 49.711HZ 0.152HZ VSG control 50.269HZ 49.864HZ 0.051HZ VSG control and introduction of wind power 50.227HZ 49.877HZ 0.021HZ Improved VSG control 50.245HZ 49.872HZ 0.019HZ Improved VSG control and introduction of wind power 50.190HZ 49.902HZ 0.016HZ

[0250] It can be seen that when using the traditional droop control strategy, there is a certain steady-state frequency deviation, and automatic recovery cannot be achieved, which is consistent with the characteristics of traditional droop control. When using VSG control, although the microgrid frequency can be closer to the power frequency, the frequency will fluctuate significantly during load switching and off-grid operation. Among the three frequency indicators, the closer the highest load minimum value is to the power frequency, the closer the average frequency deviation is to 0, and the better the control effect. After using the wind-storage coordinated frequency regulation strategy, the fluctuations generated by the microgrid during operating condition changes are reduced, and the frequency is approximately a straight line during normal operation, and the steady-state deviation is also reduced. This shows that the microgrid frequency stability control method considering wind-storage coordination proposed in this embodiment can more effectively reduce the frequency fluctuations of the microgrid and improve the power quality of the microgrid.

[0251] Figure 8The dynamic power output curves of a VSG microgrid over time are presented under five operating conditions: traditional droop control, VSG control, VSG control with wind power integration, improved VSG control, and improved VSG control with wind power integration. Under the influence of changes in microgrid operating conditions, the output power of each control strategy experiences a rapid drop. Traditional droop control exhibits the largest power drop and the most severe dynamic oscillations, with a significant power drop occurring at 1.5 seconds. VSG control, by introducing virtual inertia and damping characteristics, effectively suppresses the power drop amplitude and oscillation intensity, demonstrating superior dynamic response characteristics compared to traditional droop control. After introducing wind power to replicate frequency regulation, the steady-state level of output power under VSG control improves, but some dynamic fluctuations still exist. The improved VSG control strategy further optimizes the virtual inertia and damping characteristics. The adaptive adjustment capability of the voltage effectively suppresses overshoot and oscillation during power drop phases, resulting in faster dynamic recovery, smaller steady-state power fluctuations, and significantly enhanced robustness. In scenarios where wind power-assisted frequency regulation is introduced, the improved VSG control can still maintain stable power output, with a steady-state power level higher than that of traditional control strategies. The overshoot during the dynamic process is significantly reduced, fully verifying that this strategy can effectively smooth power fluctuations, improve the dynamic stability and power supply reliability of microgrids in microgrid scenarios with a high proportion of wind power, and provide better technical support for the stable operation of microgrids under complex operating conditions.

[0252] Figure 9 The dynamic frequency variation curves of the microgrid over time are shown under five operating conditions: traditional droop control, VSG control, VSG control with wind power integration, improved VSG control, and improved VSG control with wind power integration. When the microgrid operating conditions change, the frequency fluctuates to varying degrees under each control strategy: traditional droop control exhibits the largest frequency drop and the most severe oscillations, with a maximum frequency deviation exceeding 0.2Hz. Furthermore, it deviates from the rated value for a long period after disturbances and cannot quickly recover to steady state, resulting in the worst frequency stability. VSG control, by introducing virtual inertia and damping characteristics, significantly suppresses the depth and amplitude of frequency drops, and its dynamic frequency response characteristics are significantly better than traditional droop control. However, it still exhibits significant frequency fluctuations after disturbances, and its steady-state accuracy is insufficient. After introducing wind power-assisted frequency regulation, the frequency fluctuations of VSG control are reduced. The improved VSG control strategy effectively suppresses frequency overshoot and drop during the operating disturbance phase by optimizing the adaptive adjustment capability of virtual inertia and damping coefficient. It has a faster dynamic recovery speed, reduced steady-state frequency fluctuation, and always operates closely around the 50Hz rated value, significantly improving robustness and stability. In the scenario of introducing wind power-assisted frequency regulation, the improved VSG control can maintain excellent frequency support performance, with frequency fluctuation amplitude far less than that of traditional control strategies, fully verifying the effectiveness of the proposed strategy.

[0253] Example 2:

[0254] This embodiment provides a computer-readable storage medium storing computer instructions that, when executed by a processor, implement the steps of the microgrid frequency stability control method considering wind and energy storage synergy as described in any of the embodiments.

[0255] Example 3:

[0256] This embodiment provides a computer device, including:

[0257] Memory, used to store computer instructions;

[0258] A processor is configured to execute the computer instructions to implement the steps of the microgrid frequency stability control method considering wind and energy storage synergy as described in any one of Embodiments 1.

[0259] Example 4:

[0260] This embodiment provides a computer program product, including computer instructions, characterized in that, when the computer instructions are executed by a processor, they implement the steps of the microgrid frequency stability control method considering wind and energy storage synergy as described in any one of Embodiment 1.

[0261] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0262] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0263] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0264] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0265] The embodiments of the present invention have been described above with reference to the accompanying drawings. However, the present invention is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of the present invention without departing from the spirit and scope of the claims. All of these forms are within the protection scope of the present invention.

Claims

1. A microgrid frequency stability control method considering wind and energy storage synergy, characterized in that, include: A droop control module is introduced into the active power outer loop of the rotor-side converter of the doubly fed wind turbine in the microgrid to construct the droop response relationship between the actual output power of the wind turbine and the angular frequency deviation of the microgrid. Based on the grid-connected equivalent circuit of the virtual synchronous generator (VSG), a steady-state model of the VSG system is constructed. The droop response relationship is introduced into the rotor motion equation of the VSG system steady-state model, and small-signal analysis is performed on the VSG system steady-state model after the introduction to obtain the wind-storage coupled small-signal system. The active power output transfer function, which includes the droop response coefficient of the wind turbine, is obtained from the wind-storage coupled small-signal system. Based on the wind-storage coupled small-signal system and the active power output transfer function including the wind turbine droop response coefficient, the range of values ​​for the virtual inertia and damping coefficient of the VSG is obtained. Based on the range of values ​​for the virtual inertia and damping coefficient of the VSG, as well as the frequency deviation and frequency change rate of the microgrid, fuzzy rules are set to construct a fuzzy logic controller. Based on the real-time microgrid frequency deviation and microgrid frequency change rate, the virtual inertia and damping coefficient in the VSG are adjusted using a fuzzy logic controller.

2. The microgrid frequency stability control method considering wind and energy storage synergy according to claim 1, characterized in that, The relationship between the actual output power of the wind turbine and the droop response of the microgrid angular frequency deviation is shown in the following formula: （1）， （2）， in, This indicates the additional active power compensation amount for the wind turbine. This represents the sag coefficient of the wind turbine. Indicates the microgrid angular frequency deviation. This indicates the actual output power of the wind turbine. This represents the reference value for comprehensive active power.

3. The microgrid frequency stability control method considering wind and energy storage synergy according to claim 2, characterized in that, The step of constructing a steady-state model of the VSG system based on the grid-connected equivalent circuit of the virtual synchronous generator (VSG) includes: Based on the grid-connected equivalent circuit of the virtual synchronous generator (VSG) and Kirchhoff's voltage law, the expression for the output voltage of the VSG is derived as follows: （3）， in, This indicates the output voltage of the VSG. This represents the voltage at the point of common coupling. This indicates the output current of the VSG. This represents the virtual synchronous reactance, and j represents the imaginary unit; Based on the expression for the output voltage of the VSG, the expression for the output current of the VSG is obtained as follows: （4）， Substituting the phase angle into the expression for the output current of the VSG, we get: （5）， in, express and The phase difference between them; According to formula (5), the expression for the apparent power of the VSG output is as follows: （6）， in, This indicates the apparent power output of the VSG; Using Euler's formula to simplify equation (6), we get: （7）， according to By comparing formula (7) By taking the real and imaginary parts of the expression, we obtain the following expression for the active power of the VSG: （8）， in, This indicates the active power of the VSG; The expression for the reactive power of VSG is as follows: （9）， in, This indicates the reactive power of the VSG; By combining the expressions for active power and reactive power of the VSG, we obtain the steady-state model of the VSG system: 。 4. The microgrid frequency stability control method considering wind and energy storage synergy according to claim 3, characterized in that, The process involves incorporating the droop response relationship into the rotor motion equations of the VSG system steady-state model, and performing small-signal analysis on the resulting VSG system steady-state model to obtain a wind-storage coupled small-signal system, including: According to the steady-state model of the VSG system, at the steady-state operating point Linearization of the vicinity yields: （10）， in, This represents the change in power. , To represent partial derivatives, This represents the change in phase angle. ; Let the synchronization coefficient ,get The expression is: （11）， Transforming formula (11) into the complex frequency domain, we obtain the following expression: （12）， in, Represents complex variables in the complex plane. This represents the change in power in the complex frequency domain. This represents the change in phase angle in the complex frequency domain; The expression for the relationship between angular velocity and power angle in VSG is as follows: （13）， in, Indicates the actual angular velocity. Indicates the initial angular velocity; Linearizing equation (13), we get: （14） in, Indicates the microgrid angular frequency deviation; The expression for the rotor motion equation of VSG is as follows: （15）， in, This indicates the mechanical power of the VSG. This indicates the electromagnetic power of the VSG. Indicates the damping coefficient. Represents virtual inertia; Introducing the droop response relationship into formula (15) and linearizing it, we obtain the linearized equation for wind-storage coupling: （16） in, This represents the change in the mechanical power of the VSG. This indicates the change in the electromagnetic power of the VSG; Combining equations (11), (14), and (16), we obtain the wind-storage coupled small-signal system: 。 5. The microgrid frequency stability control method considering wind and energy storage synergy according to claim 4, characterized in that, The process of obtaining the active power output transfer function, which includes the droop response coefficient of the wind turbine, based on the wind-storage coupled small-signal system includes: Taking the Laplace transform of equation (13) yields: （17）， in, Represents the angular velocity in the complex frequency domain; Taking the Laplace transform of equation (15) yields: （18）， Combining equations (12), (17), and (18), we get: （19）， According to formula (19), the active power output transfer function including the droop response coefficient of the wind turbine is obtained as follows: （20）， in, This represents the active power output transfer function that includes the sag response coefficient of the wind turbine.

6. The microgrid frequency stability control method considering wind and energy storage synergy according to claim 1, characterized in that, The range of values ​​for the virtual inertia and damping coefficient of the VSG, obtained based on the wind-storage coupled small-signal system and the active power output transfer function including the wind turbine droop response coefficient, includes: Treating the wind-storage coupled small-signal system as a standard second-order system, its key indicators include the oscillation frequency of the VSG. Peak time 2% steady-state time and overshoot ; According to the oscillation frequency of the VSG Peak time 2% steady-state time and overshoot Damping ratio with VSG and natural oscillation angular frequency The relationship between the two factors yields the damping ratio. The optimal range of values ​​is Natural oscillation angular frequency The optimal range of values ​​is ; According to the damping ratio The optimal range of values ​​and natural oscillation angular frequency The optimal range of values ​​and the damping ratio Natural oscillation angular frequency Virtual inertia Damping coefficient and wind turbine sag coefficient The relationship is used to obtain the virtual inertia. The per-unit value range is Virtual inertia The actual range of values ​​is Damping coefficient The per-unit value range is Damping coefficient The actual range of values ​​is ; The damping ratio The expression is: （21）， in, Indicates the synchronization coefficient; The natural oscillation angular frequency The expression is: （22）， The oscillation frequency of the VSG The expression is: （23）， The peak time The expression is: （24）， The 2% steady-state time The expression is: （25）， The overshoot The expression is: （26）， in, This represents the natural exponential function.

7. The microgrid frequency stability control method considering wind and energy storage synergy according to claim 1, characterized in that, The step of setting fuzzy rules based on the range of values ​​for the virtual inertia and damping coefficient of the VSG, as well as the microgrid frequency deviation and microgrid frequency change rate, and constructing a fuzzy logic controller includes: The microgrid frequency deviation and microgrid frequency change rate are divided into five input language values, including negative large NB, negative small NS, zero Z, positive small PS and positive large PB; virtual inertia and damping coefficient It is divided into five output language values, including minimal VS, minor S, medium M, large L and maximum VL; Based on the coordinated droop response of wind turbines, the larger the frequency change rate of the microgrid, the greater the virtual inertia. Based on the principle that the larger the frequency deviation, the greater the total equivalent damping required by the system, a virtual inertia is set. and damping coefficient Fuzzy rules; Based on virtual inertia and damping coefficient The fuzzy rules, with microgrid frequency deviation and microgrid frequency change rate as inputs, and virtual inertia. and damping coefficient To generate the output, construct a fuzzy logic controller; The virtual inertia The fuzzy rules are as follows: If the frequency deviation is NB and the frequency change rate is NB, then Let VL be the frequency deviation; if the frequency deviation is NB and the frequency change rate is NS, then... Let L be the frequency deviation; if the frequency deviation is NB and the frequency change rate is Z, then... Let L be the frequency deviation; if the frequency deviation is NB and the frequency change rate is PS, then Let M be the frequency deviation; if the frequency deviation is NB and the frequency change rate is PB, then... For M; If the frequency deviation is NS and the frequency change rate is NB, then Let L be the frequency deviation; if the frequency deviation is N / S and the frequency change rate is N / S, then Let L be the frequency deviation; if the frequency deviation is N / S and the frequency change rate is Z, then Let M be the frequency deviation; if the frequency deviation is N / S and the frequency change rate is PS, then... Let M be the frequency deviation; if the frequency deviation is NS and the frequency change rate is PB, then... S; If the frequency deviation is Z and the frequency change rate is NB, then Let L be the frequency deviation; if the frequency deviation is Z and the frequency change rate is NS, then Let M be the frequency deviation; if the frequency deviation is Z and the frequency change rate is Z, then... Let VS be the frequency deviation; if the frequency deviation is Z and the frequency change rate is PS, then Let M be the frequency deviation; if the frequency deviation is Z and the frequency change rate is PB, then... Let L be the value. If the frequency deviation is PS and the frequency change rate is NB, then Let M be the frequency deviation; if the frequency deviation is PS and the frequency change rate is NS, then... Let M be the frequency deviation; if the frequency deviation is PS and the frequency change rate is Z, then... Let M be the frequency deviation; if the frequency deviation is PS and the frequency change rate is PS, then Let L be the frequency deviation; if the frequency deviation is PS and the frequency change rate is PB, then Let L be the value. If the frequency deviation is PB and the frequency change rate is NB, then Let M be the frequency deviation; if the frequency deviation is PB and the frequency change rate is NS, then... Let S be the frequency deviation; if the frequency deviation is PB and the frequency change rate is Z, then... Let L be the frequency deviation; if the frequency deviation is PB and the frequency change rate is PS, then Let L be the frequency deviation; if the frequency deviation is PB and the frequency change rate is PB, then VL; The damping coefficient The fuzzy rules are as follows: If the frequency deviation is NB and the frequency change rate is NB, then Let VL be the frequency deviation; if the frequency deviation is NB and the frequency change rate is NS, then... Let L be the frequency deviation; if the frequency deviation is NB and the frequency change rate is Z, then... Let L be the frequency deviation; if the frequency deviation is NB and the frequency change rate is PS, then Let M be the frequency deviation; if the frequency deviation is NB and the frequency change rate is PB, then... S; If the frequency deviation is NS and the frequency change rate is NB, then Let L be the frequency deviation; if the frequency deviation is N / S and the frequency change rate is N / S, then Let M be the frequency deviation; if the frequency deviation is N / S and the frequency change rate is Z, then... Let M be the frequency deviation; if the frequency deviation is N / S and the frequency change rate is PS, then... Let S be the frequency deviation; if the frequency deviation is N / S and the frequency change rate is PB, then... For VS; If the frequency deviation is Z and the frequency change rate is NB, then Let L be the frequency deviation; if the frequency deviation is Z and the frequency change rate is NS, then Let M be the frequency deviation; if the frequency deviation is Z and the frequency change rate is Z, then... Let M be the frequency deviation; if the frequency deviation is Z and the frequency change rate is PS, then... Let M be the frequency deviation; if the frequency deviation is Z and the frequency change rate is PB, then... Let L be the value. If the frequency deviation is PS and the frequency change rate is NB, then Let VS be the frequency deviation; if the frequency deviation is PS and the frequency change rate is NS, then Let S be the frequency deviation; if the frequency deviation is PS and the frequency change rate is Z, then... Let M be the frequency deviation; if the frequency deviation is PS and the frequency change rate is PS, then Let M be the frequency deviation; if the frequency deviation is PS and the frequency change rate is PB, then... Let L be the value. If the frequency deviation is PB and the frequency change rate is NB, then Let S be the frequency deviation; if the frequency deviation is PB and the frequency change rate is NS, then... Let M be the frequency deviation; if the frequency deviation is PB and the frequency change rate is Z, then... Let L be the frequency deviation; if the frequency deviation is PB and the frequency change rate is PS, then Let L be the frequency deviation; if the frequency deviation is PB and the frequency change rate is PB, then VL.

8. A computer-readable storage medium storing computer instructions thereon, characterized in that, When the computer instruction is executed by the processor, it implements the steps of the microgrid frequency stability control method considering wind and energy storage synergy as described in any one of claims 1-7.

9. A computer device, characterized in that, include: Memory, used to store computer instructions; A processor for executing the computer instructions to implement the steps of the microgrid frequency stability control method considering wind-storage synergy as described in any one of claims 1-7.

10. A computer program product comprising computer instructions, characterized in that, When the computer instruction is executed by the processor, it implements the steps of the microgrid frequency stability control method considering wind and energy storage synergy as described in any one of claims 1-7.

Images