Method and system for improving transient stability of multi-machine system by combining superconducting energy storage

Abstract

The invention discloses a method and a system for improving transient stability of a multi-machine system by combining superconducting energy storage. The method comprises the following steps: establishing a multi-machine system model containing direct-driven wind power under a VSG control strategy; wherein a VSG control strategy is adopted by a grid-side converter of the multi-machine system model; establishing a superconducting energy storage system model; setting a dynamic power compensation control strategy of a converter VSC in the superconducting energy storage system model based on sliding mode control; configuring the energy storage power and capacity of the superconducting energy storage system model; and constructing a joint model comprising the multi-machine system model and a superconducting energy storage system model, so that the multi-machine system model can be in a transient stable state based on the joint model. According to the combined control strategy based on sliding mode control, high-precision dynamic adjustment of the superconducting energy storage system is realized, and the strategy can quickly respond in a complex fault scene, effectively relieve power fluctuation and guarantee stable operation of a power system.

Description

Technical Field

[0001] The present invention relates to the technical field of direct-drive wind power generation systems, and more particularly, to a method and system for improving the transient stability of a multi-machine system by combining superconducting energy storage. Background Art

[0002] With the transformation of the global energy structure towards low-carbon and renewable directions, the penetration rates of new energy power generation such as wind power and photovoltaic power are continuously increasing, and gradually become the main energy forms in the power system. However, due to the inherent characteristics of randomness, volatility, and intermittency of new energy power generation, the operation stability of the power system faces severe challenges. In a multi-machine power system with a high proportion of new energy, the transient stability problem is particularly prominent. Especially in the case of a short-circuit fault or a large power fluctuation, the fluctuations of the grid frequency and voltage are significantly intensified, posing a threat to the safe operation of the system.

[0003] As a mainstream wind power technology, the direct-drive wind power generation system (PMSG) is completely decoupled from the power grid because it is connected to the grid through an inverter, and its inertial response characteristics are greatly weakened, and it cannot provide physical inertia support for the power grid like a traditional synchronous generator. When the power grid is disturbed, the dynamic performance of the direct-drive wind turbine shows a lag in frequency response and insufficient voltage regulation ability, which is prone to cause frequency oscillation and power imbalance problems. In addition, with the increase in the proportion of wind power access, the equivalent inertia of the power grid decreases significantly, further exacerbating the dynamic vulnerability of the system.

[0004] As an efficient energy storage technology, the superconducting magnetic energy storage system (SMES) has unique advantages in the dynamic regulation ability during the transient process of the power system due to its characteristics of millisecond-level response, high power density, and high energy storage efficiency. By quickly adjusting the power output, SMES can suppress the grid frequency fluctuation and compensate for the power gap in a short time, providing important support for improving the system stability. However, existing research mainly focuses on the application of SMES to traditional synchronous machine systems. For multi-machine systems containing direct-drive wind power, its optimized control strategy and engineering application scheme are not yet mature, and there are a series of technical problems.

[0005] Therefore, how to make full use of the fast response ability of the superconducting energy storage system to improve the transient stability of the multi-machine system is an urgent problem to be solved. Summary of the Invention

[0006] The present invention proposes a method and system for improving the transient stability of a multi-machine system by combining superconducting energy storage to solve the problem of how to improve the transient stability of a multi-machine system containing wind power.

[0007] To solve the above problems, according to one aspect of the present invention, there is provided a method for improving the transient stability of a multi-machine system by combining superconducting energy storage, the method comprising:

[0008] Build a multi - machine system model with direct - drive wind power under the VSG control strategy; among them, the grid - side converter of the multi - machine system model adopts the VSG control strategy;

[0009] Build a superconducting energy storage system model;

[0010] Based on sliding - mode control, set the dynamic power compensation control strategy for the converter VSC in the superconducting energy storage system model;

[0011] Configure the energy storage power and capacity of the superconducting energy storage system model;

[0012] Construct a combined model including the multi - machine system model and the superconducting energy storage system model, so that the multi - machine system model can be in a transient stable state based on the combined model.

[0013] Preferably, the multi - machine system model includes: a wind turbine model, a permanent - magnet synchronous motor model, a back - to - back converter model including a machine - side converter and a grid - side converter, a DC capacitor model, a filter inductor model, a wind farm inertia response model, a machine - side converter overspeed load - shedding control model, and a grid - side converter VSG control model.

[0014] Preferably, the establishment of the superconducting energy storage system model includes:

[0015] Establish a current model for the AC side of the converter, an output voltage model for the AC side of the VSC, a dynamic power balance model for the AC - DC sides, a dynamic model of the VSC, a magnetization model of the superconducting magnet, a demagnetization model of the superconducting magnet, and a duty - cycle model of the chopper pulse.

[0016] Preferably, the setting of the dynamic power compensation control strategy for the converter VSC in the superconducting energy storage system model based on sliding - mode control includes:

[0017] Establish a voltage outer - loop control model based on the design of the sliding - mode surface:

[0018]

[0019] Establish a sliding - mode surface model:

[0020]

[0021] Establish a VSC voltage mathematical model:

[0022]

[0023] Establish a voltage outer - loop output model:

[0024]

[0025] Establish a complex power exponential reaching law model:

[0026]

[0027] Establish a sliding mode switching model:

[0028]

[0029] Establish a VSC current mathematical model:

[0030]

[0031] Establish a control law model:

[0032]

[0033] Wherein, L, R, and C respectively represent the filter inductance value, the equivalent internal resistance of the inductor, the switching loss value, and the DC-side capacitor value; i d 、i q are the currents on the grid side d and q axes respectively; u sd 、u sq are the power supply voltages on the grid side d and q axes respectively; s d 、s q are the switching functions on the d and q axes; S u (x), e u are the sliding mode surface model based on the DC-side capacitor voltage and its intermediate variable respectively; S u′ (x) is the voltage outer-loop sliding mode surface model; u dc 、i dc are the voltage and current on the DC side of the chopper respectively; is the reference value of the voltage on the DC side of the chopper; λ is the feedback coefficient; s is the sliding mode surface; is the complex power exponential reaching law of the sliding mode motion; ε1, ε2 are the reaching coefficients; α, β are the high-order reaching coefficients; k is the exponential reaching coefficient; sgns is the sign function; s1, s2 are the intermediate variables of the sliding mode switching model; is the derivative of this intermediate variable; s d 、s q are the switching functions on the d and q axes respectively; are the current reference values on the grid side d and q axes respectively; ω is the grid-side voltage angular frequency; u td 、u tq are the output voltages on the VSC AC side d and q axes respectively.

[0034] Preferably, configuring the energy storage power and capacity of the superconducting energy storage system model includes:

[0035] Establish a control law model:

[0036] PSN = max{P smes (t)},

[0037] Establish the SOC model of the SMES:

[0038]

[0039] Establish the charge / discharge amount model:

[0040]

[0041] Establish the energy storage constraint model:

[0042]

[0043]

[0044] where P smes (t) is the reference power of the SMES at time t; P SN is the rated power of the SMES; SOC(t) is the state of charge of the SMES at time t; SOC0 is the initial state of charge of the SMES; E SN is the rated capacity of the SMES; E H (t) is the maximum cumulative charge; E L (t) is the maximum cumulative discharge of the SMES; i max , i min and i0 are the maximum value, minimum value and initial value of the magnet current respectively.

[0045] According to another aspect of the present invention, there is provided a system for improving the transient stability of a multi-machine system by combining superconducting energy storage. The system includes:

[0046] A multi-machine system model establishment unit for establishing a multi-machine system model including direct-drive wind power under the VSG control strategy; wherein, the grid-side converter of the multi-machine system model adopts the VSG control strategy;

[0047] A superconducting energy storage system model establishment unit for establishing a superconducting energy storage system model;

[0048] A sliding mode control unit for setting the dynamic power compensation control strategy of the converter VSC in the superconducting energy storage system model based on sliding mode control;

[0049] A configuration unit for configuring the energy storage power and capacity of the superconducting energy storage system model;

[0050] A combined model establishment unit for constructing a combined model including the multi-machine system model and the superconducting energy storage system model, so that the multi-machine system model can be in a transient stable state based on the combined model.

[0051] Preferably, the multi-machine system model includes: a wind turbine model, a permanent magnet synchronous motor model, a back-to-back converter model including a machine-side converter and a grid-side converter, a DC capacitor model, a filter inductor model, a wind farm inertia response model, a machine-side converter overspeed load shedding control model, and a grid-side converter VSG control model.

[0052] Preferably, the superconducting energy storage system model building unit builds a superconducting energy storage system model, including:

[0053] Building a current model on the AC side of the converter, a VSC AC side output voltage model, a dynamic power balance model on the AC and DC sides, a dynamic model of the VSC, a magnetization model of the superconducting magnet, a demagnetization model of the superconducting magnet, and a duty ratio model of the chopper pulse.

[0054] Preferably, the sliding mode control unit sets the dynamic power compensation control strategy of the converter VSC in the superconducting energy storage system model based on sliding mode control, including:

[0055] Building a voltage outer loop control model based on the design of the sliding mode surface:

[0056]

[0057] Building a sliding mode surface model:

[0058]

[0059] Building a VSC voltage mathematical model:

[0060]

[0061] Building a voltage outer loop output model:

[0062]

[0063] Building a complex power exponential reaching law model:

[0064]

[0065] Building a sliding mode switching model:

[0066]

[0067] Building a VSC current mathematical model:

[0068]

[0069] Building a control rate model:

[0070]

[0071] Among them, L, R, and C respectively represent the filter inductance value, the equivalent internal resistance of the inductor and the switching loss value, and the DC-side capacitance value; i d , i q are respectively the currents on the grid-side d and q axes; u sd , u sq are respectively the power supply voltages on the grid-side d and q axes; s d , s q are the switching functions on the d and q axes; S u (x), e u are respectively the sliding mode surface model based on the DC-side capacitor voltage and its intermediate variable; S u′ (x) is the voltage outer-loop sliding mode surface model; u dc , i dc are respectively the voltage and current on the DC side of the chopper; is the reference value of the voltage on the DC side of the chopper; λ is the feedback coefficient; s is the sliding mode surface; is the complex power exponential reaching law of the sliding mode motion; ε1, ε2 are the reaching coefficients; α, β are the high-order reaching coefficients; k is the exponential reaching coefficient; sgns is the sign function; s1, s2 are the intermediate variables of the sliding mode switching model; is the derivative of this intermediate variable; s d , s q are respectively the switching functions on the d and q axes; are respectively the current reference values on the grid-side d and q axes; ω is the grid-side voltage angular frequency; u td , u tq are respectively the output voltages on the VSC AC-side d and q axes.

[0072] Preferably, the configuration unit configures the energy storage power and capacity of the superconducting energy storage system model, including:

[0073] Establish a control rate model:

[0074] P SN = max{P smes (t)},

[0075] Establish an SOC model of SMES:

[0076]

[0077] Establish a charge / discharge amount model:

[0078]

[0079] Establish an energy storage constraint model:

[0080]

[0081] Among them, P smes (t) is the reference power of the SMES at time t; P SN is the rated power of the SMES; SOC(t) is the state of charge of the SMES at time t; SOC0 is the initial state of charge of the SMES; E SN is the rated capacity of the SMES; E H (t) is the maximum cumulative charge; E L (t) is the maximum cumulative discharge of the SMES; i max , i min and i0 are the maximum value, minimum value and initial value of the magnet current respectively.

[0082] Based on another aspect of the present invention, the present invention provides a computer-readable storage medium, on which a computer program is stored, and when the program is executed by a processor, the steps of any one of the methods for improving the transient stability of a multi-machine system by combining superconducting energy storage are realized.

[0083] Based on another aspect of the present invention, the present invention provides an electronic device, including:

[0084] The above-mentioned computer-readable storage medium; and

[0085] One or more processors for executing the program in the computer-readable storage medium.

[0086] The present invention provides a method and system for improving the transient stability of a multi-machine system by combining superconducting energy storage, including: establishing a multi-machine system model including direct-drive wind power under a VSG control strategy; wherein, the grid-side converter of the multi-machine system model adopts a VSG control strategy; establishing a superconducting energy storage system model; setting a dynamic power compensation control strategy for the converter VSC in the superconducting energy storage system model based on sliding mode control; configuring the energy storage power and capacity of the superconducting energy storage system model; constructing a combined model including the multi-machine system model and the superconducting energy storage system model, so that the multi-machine system model can be in a transient stable state based on the combined model. The present invention makes full use of the fast dynamic regulation ability of the superconducting energy storage system and the power slope recovery characteristic of the wind turbine, can significantly alleviate the frequency oscillation and voltage deviation problems caused by short-circuit faults and wind power fluctuations, and realizes a significant improvement in the transient stability of the multi-machine power system; the combined control strategy based on sliding mode control of the present invention calculates the dynamic compensation power through the system frequency deviation in the outer loop, and combines the current feedback with the sliding mode surface control in the inner loop to realize the high-precision dynamic regulation of the superconducting energy storage system. This strategy can quickly respond in complex fault scenarios, effectively alleviate power fluctuations, and ensure the stable operation of the power system; through the optimized configuration of the SMES power and capacity of the present invention, it can ensure its efficient operation under different disturbance scenarios. Description of the Drawings

[0087] The exemplary embodiments of the present invention can be more fully understood by reference to the following drawings:

[0088] Figure 1 FIG. 5 is a flowchart of a method 100 for improving the transient stability of a multi-machine system by combined superconducting energy storage according to an embodiment of the present invention;

[0089] Figure 2 FIG. 9 is a topology diagram of a direct-drive wind turbine grid-connected system according to an embodiment of the present invention;

[0090] Figure 3 FIG. 13 is an equivalent circuit diagram of a PMSG according to an embodiment of the present invention;

[0091] Figure 4 FIG. 17 is a block diagram of a machine-side converter control system according to an embodiment of the present invention;

[0092] Figure 5 FIG. 21 is a block diagram of a grid-side converter control system according to an embodiment of the present invention;

[0094] Figure 6 FIG. 25 is a schematic diagram of active and reactive power control of VSG control according to an embodiment of the present invention;

[0095] Figure 7 FIG. 29 is a circuit topology diagram of SMES using VSC and a traditional chopper according to an embodiment of the present invention;

[0096] Figure 8 FIG. 33 is a diagram of three switching states of a chopper according to an embodiment of the present invention;

[0097] Figure 9 FIG. 37 is a block diagram of a sliding mode control system for the voltage outer loop of VSC for SMES according to an embodiment of the present invention;

[0098] Figure 10 FIG. 41 is a block diagram of a sliding mode control system for the current inner loop of VSC for SMES according to an embodiment of the present invention;

[0099] Figure 11 FIG. 45 is a diagram of a three-machine nine-node system for simulation according to an embodiment of the present invention;

[0100] Figure 12 FIG. 49 is a diagram of the simulation results with the energy storage cooperative active power recovery control strategy applied according to an embodiment of the present invention;

[0101] Figure 13 FIG. 53 is a diagram of the simulation results without the energy storage cooperative active power recovery control strategy applied according to an embodiment of the present invention;

[0102] Figure 14 FIG. 57 is a schematic structural diagram of a system 1400 for improving the transient stability of a multi-machine system by combined superconducting energy storage according to an embodiment of the present invention. Detailed implementation manners

[0103] Now, exemplary implementation manners of the present invention will be described with reference to the accompanying drawings. However, the present invention can be implemented in many different forms and is not limited to the embodiments described herein. These embodiments are provided to disclose the present invention in detail and completely, and to fully convey the scope of the present invention to those skilled in the art. The terms in the exemplary implementation manners shown in the accompanying drawings are not limitations on the present invention. In the drawings, the same units / components are denoted by the same reference numerals.

[0104] Unless otherwise specified, the terms (including scientific and technical terms) used herein have the ordinary meaning understood by those skilled in the art. Additionally, it can be understood that the terms defined in a commonly used dictionary should be understood to have a meaning consistent with the context of their related fields, and should not be understood in an idealized or overly formal sense.

[0105] Figure 1 FIG. 100 is a flowchart of a method for improving the transient stability of a multi-machine system by combining superconducting energy storage according to an embodiment of the present invention. As Figure 1 Therefore, the method for improving the transient stability of a multi-machine system by combining superconducting energy storage provided by the embodiment of the present invention makes full use of the fast dynamic regulation ability of the superconducting energy storage system and the power slope recovery characteristic of the wind turbine, and can significantly alleviate the frequency oscillation and voltage deviation problems caused by short-circuit faults and wind power fluctuations, realizing a significant improvement in the transient stability of the multi-machine power system; the combined control strategy based on sliding mode control of the present invention calculates the dynamic compensation power through the system frequency deviation in the outer loop, and combines the current feedback with the sliding mode surface control in the inner loop to achieve high-precision dynamic regulation of the superconducting energy storage system. This strategy can quickly respond in complex fault scenarios, effectively alleviate power fluctuations, and ensure the stable operation of the power system; through the optimized configuration of the SMES power and capacity, the present invention can ensure its efficient operation under different disturbance scenarios. The method 100 for improving the transient stability of a multi-machine system by combining superconducting energy storage provided by the embodiment of the present invention starts from step 101. In step 101, a multi-machine system model including direct-drive wind power under the VSG control strategy is established; wherein, the grid-side converter of the multi-machine system model adopts the VSG control strategy.

[0106] Preferably, the multi-machine system model includes: a wind turbine model, a permanent magnet synchronous motor model, a back-to-back converter model including a machine-side converter and a grid-side converter, a DC capacitor model, a filter inductor model, a wind farm inertia response model, a machine-side converter overspeed load shedding control model, and a grid-side converter VSG control model.

[0107] In the present invention, a mathematical model of a permanent magnet synchronous generator (PMSG) under the VSG control strategy is first established. The direct-drive wind power generation system under VSG control consists of a wind turbine, a permanent magnet synchronous motor, a machine-side converter, a grid-side converter, and a DC capacitor. Among them, the grid-side converter adopts the VSG control strategy, and the topology of the direct-drive wind turbine grid-connected system is as shown in Figure 2 shown.

[0108] In the present invention, the specific process of establishing the mathematical model of the permanent magnet synchronous generator (PMSG) under the VSG control strategy includes:

[0109] Step 1.1: Establish a wind turbine model using Equation (1):

[0110]

[0111] In Equation (1), C po represents the wind energy utilization coefficient, ρ represents the air density, v w represents the wind speed, and r represents the radius of the wind turbine blade;

[0112] Step 1.2: For the equivalent circuit of the PMSG in Figure 3 , establish a permanent magnet synchronous motor model using Equation (2):

[0113]

[0114] In Equation (2), L d , L q are the d-axis and q-axis components of the synchronous inductance respectively, ψ f is the magnetic flux of the PMSG, N p is the number of pole pairs of the generator, ω r is the rotational speed of the wind turbine, and R s is the stator resistance;

[0115] Step 1.3: Establish a back-to-back converter model. The control system block diagram of the machine-side converter is as shown in Figure 4 shown, and the control system block diagram of the grid-side converter is as shown in Figure 5 shown;

[0116] Step 1.4: Establish a DC capacitor model using Equation (3):

[0117]

[0118] In Equation (3), C dc represents the capacitance value of the DC capacitor, p s is the active power output by the PMSG, and P g represents the grid-connected output power;

[0119] Step 1.5: Establish a filter inductor model using Equation (4):

[0120]

[0121] Step 1.6. Establish a wind farm inertia response model using Equation (5):

[0122]

[0123] In Equation (5), ΔP is the change in active power of the wind farm, T J is the inertia time constant, f N is the rated grid frequency, f is the grid connection point frequency of the wind farm, and P N is the rated capacity of the wind farm.

[0124] Step 1.7. Establish a rotor side converter overspeed load shedding control model using Equation (6):

[0125]

[0126] In Equation (6), P ref is the reference power after overspeed load shedding control, C po is the wind energy utilization coefficient after overspeed load shedding control, d is the load shedding coefficient, and r is the radius of the wind turbine blade.

[0127] Step 1.8. For the Figure 6 VSG control system in, establish a grid side converter VSG control model using Equation (7):

[0128]

[0129] In Equation (7), J is the inertia coefficient, D is the damping coefficient, P e , P ref are the active power output value and the active power reference value, Q e , Q ref are the reactive power output value and the reactive power reference value, u dc , u dc_ref are the DC side voltage and the DC side voltage set value, and ω ref is the angular velocity reference value.

[0130] In Step 102, establish a superconducting energy storage system model.

[0131] Preferably, establishing the superconducting energy storage system model includes:

[0132] Establish a current model on the AC side of the converter, an output voltage model on the AC side of the VSC, a dynamic power balance model between the AC and DC sides, a dynamic model of the VSC, a magnetization model of the superconducting magnet, a demagnetization model of the superconducting magnet, and a duty cycle model of the chopper pulse.

[0133] In the present invention, a mathematical model of a superconducting magnetic energy storage system (SMES) is established. Among them, the circuit topology of the SMES using VSC and traditional choppers is as Figure 7 shown.

[0134] In the present invention, the specific process of establishing the mathematical model of the superconducting magnetic energy storage system (SMES) includes:

[0135] Step 2.1: Establish the current model of the AC side of the converter using Equation (8):

[0136]

[0137] In Equation (8), L is the filtering inductance on the AC side, C is the DC bus capacitance, and the binary switching logic function s is defined k :

[0138]

[0139] Step 2.2: Establish the output voltage model of the VSC AC side using Equation (10):

[0140]

[0141] Step 2.3: Establish the dynamic power balance model of the AC / DC sides using Equation (11):

[0142]

[0143] In Equation (11), p chopper is the active power exchange between the DC side chopper and the superconducting magnet and the AC system, and p loss is the power loss on the VSC AC side;

[0144] Step 2.4: Establish the dynamic model of the VSC using Equation (12):

[0145]

[0146] The three switching states of the DC / DC chopper are as Figure 8 shown. Establish the magnetization model of the superconducting magnet using Equation (13):

[0147]

[0148] In the formula, i sc is the superconducting magnet current, u dc is the DC side capacitor voltage, L sc is the superconducting magnet inductance, C is the DC side capacitor value, and R sc is the equivalent resistance of the superconducting magnet loss;

[0149] Step 2.6: Establish a demagnetization model of the superconducting magnet using Equation (14):

[0150]

[0151] Step 2.7: Establish a duty cycle model of the chopper pulse using Equation (15):

[0152]

[0153] In Step 103, based on sliding mode control, set the dynamic power compensation control strategy of the voltage source converter (VSC) in the superconducting energy storage system model.

[0154] Preferably, setting the dynamic power compensation control strategy of the voltage source converter (VSC) in the superconducting energy storage system model based on sliding mode control includes:

[0155] Establish a voltage outer loop control model based on the design of the sliding mode surface:

[0156]

[0157] Establish a sliding mode surface model:

[0158]

[0159] Establish a VSC voltage mathematical model:

[0160]

[0161] Establish a voltage outer loop output model:

[0162]

[0163] Establish a complex power exponential reaching law model:

[0164]

[0165] Establish a sliding mode switching model:

[0166]

[0167] Establish a VSC current mathematical model:

[0168]

[0169] Establish a control law model:

[0170]

[0171] Among them, L, R, and C respectively represent the filter inductance value, the equivalent internal resistance of the inductor and the switching loss value, and the DC side capacitance value; i d 、iq They are the currents on the grid side d and q axes; u sd , u sq They are the power supply voltages on the grid side d and q axes; s d , s q They are the switching functions on the d and q axes; S u (x), e u They are the sliding mode surface model based on the DC-side capacitor voltage and its intermediate variable; S u′ (x) is the voltage outer loop sliding mode surface model; u dc , i dc They are the voltage and current on the DC side of the chopper respectively; It is the reference value of the voltage on the DC side of the chopper; λ is the feedback coefficient; s is the sliding mode surface; It is the complex power exponential reaching law of the sliding mode motion; ε1, ε2 are the reaching coefficients; α, β are the high-order reaching coefficients; k is the exponential reaching coefficient; sgns is the sign function; s1, s2 are the intermediate variables of the sliding mode switching model; It is the derivative of this intermediate variable; s d , s q They are the switching functions on the d and q axes respectively; They are the current reference values on the grid side d and q axes respectively; ω is the grid-side voltage angular frequency; u td , u tq They are the output voltages on the VSC AC side d and q axes respectively.

[0172] In the present invention, the SMES is designed with a VSC sliding mode controller. The specific process includes:

[0173] Step 3.1: Establish a voltage outer loop control model based on the sliding mode surface design using Equation (16):

[0174]

[0175] Step 3.2: Establish a sliding mode surface model using Equation (17):

[0176]

[0177] Step 3.3: Establish a VSC voltage mathematical model using Equation (18):

[0178]

[0179] Step 3.4: The voltage outer loop sliding mode variable structure control strategy based on the sliding mode surface design is as Figure 9 shown. Establish a voltage outer loop output model using Equation (19):

[0180]

[0181] Step 3.5. Establish a complex power exponential reaching law model using Equation (20):

[0182]

[0183] In Equation (20), 0 < α < 1, β > 1, ε1 > 0, ε2 > 0, k > 0. The parameter k is the reaching speed, which determines how fast the state point reaches the sliding surface; ε1|s| α , ε2|s| β are the arrival speeds, which determine the chattering intensity of moving back and forth across the sliding surface during sliding mode motion. When |s| > 1 and the distance from the sliding surface is far, the -ε2|s| β sgn(s) term plays a major role, cooperating with -ks to make the state point move quickly towards the sliding surface. Increasing β will increase the reaching speed; when |s| < 1, the -ε1|s| α sgn(s) term plays a major role, and decreasing α will increase the reaching speed.

[0184] Step 3.6. Establish a sliding mode switching model using Equation (21):

[0185]

[0186] Step 3.7. Establish a VSC current mathematical model using Equation (22):

[0187]

[0188] Step 3.8. The current inner-loop sliding mode variable structure control strategy based on the sliding surface design is as Figure 10 shown. Establish a control law model using Equation (23):

[0189]

[0190] Among them, L, R, and C respectively represent the filter inductor value, the equivalent internal resistance of the inductor and the switching loss value, and the DC side capacitor value; i d , i q are the grid-side d-axis and q-axis currents respectively; u sd , u sq are the grid-side d-axis and q-axis power supply voltages respectively; s d , s q are the switching functions on the d-axis and q-axis; S u (x), e u are the sliding surface model based on the DC side capacitor voltage and its intermediate variable respectively; S u′ (x) is the voltage outer-loop sliding surface model; u dc , i dc are the voltage and current on the DC side of the chopper respectively; is the reference value of the DC - side voltage of the chopper; λ is the feedback coefficient; s is the sliding mode surface; is the complex - power - exponential reaching law of the sliding mode motion; ε1, ε2 are the reaching coefficients; α, β are the high - order reaching coefficients; k is the exponential reaching coefficient; sgns is the sign function; s1, s2 are the intermediate variables of the sliding - mode switching model; is the derivative of this intermediate variable; s d 、s q are the switching functions on the d - axis and q - axis respectively; are the current reference values on the grid - side d - axis and q - axis respectively; ω is the grid - side voltage angular frequency; u td 、u tq are the output voltages on the VSC AC - side d - axis and q - axis respectively.

[0191] The present invention proposes a dynamic power compensation method combining a direct - drive wind turbine and a superconducting energy storage system. By combining the power - slope - recovery mechanism of the wind turbine (recovery rate is about 20% / s) with the millisecond - level fast response of the superconducting energy storage, the dynamic characteristics of frequency and voltage are synergistically regulated, ensuring the effective suppression of frequency oscillation and the rapid recovery of voltage offset, and significantly improving the dynamic recovery ability of the system.

[0192] In step 104, configure the energy storage power and capacity of the superconducting energy storage system model.

[0193] Preferably, configuring the energy storage power and capacity of the superconducting energy storage system model includes:

[0194] Establish a control - rate model:

[0195] P SN =max{|P smes (t)|},

[0196] Establish an SOC model of SMES:

[0197]

[0198] Establish a charge / discharge - quantity model:

[0199]

[0200] Establish an energy - storage constraint model:

[0201]

[0202] where, P smes (t) is the reference power of SMES at time t; P SN is the rated power of SMES; SOC(t) is the state of charge of SMES at time t; SOC0 is the initial state of charge of SMES; E SNis the rated capacity of the SMES; E H (t) is the maximum cumulative charge; E L (t) is the maximum cumulative discharge of the SMES; i max 、i min and i0 are the maximum value, minimum value, and initial value of the magnet current respectively.

[0203] In the present invention, the process of configuring the energy storage power and capacity of the SMES includes:

[0204] Step 4.1: Establish a control rate model using Equation (24):

[0205] P SN =max{|P smes (t)|} (24)

[0206] Step 4.2: Establish an SOC model of the SMES using Equation (25):

[0207]

[0208] In Equation (25), SOC0 is the initial state of charge of the SMES; E SN is the rated capacity of the SMES;

[0209] Step 4.3: Establish a charge / discharge amount model using Equation (26):

[0210]

[0211] In Equation (26), E H (t) is the maximum cumulative charge, E L (t) is the maximum cumulative discharge of the SMES, i max , i min , i0 are the maximum value, minimum value, and initial value of the magnet current respectively;

[0212] Step 4.4: Establish an energy storage constraint model using Equation (27) and Equation (28):

[0213]

[0214] In step 105, a combined model including the multi-machine system model and the superconducting energy storage system model is constructed, so that the multi-machine system model can be in a transient stable state based on the combined model.

[0215] In the present invention, by constructing a combined model including the multi-machine system model and the superconducting energy storage system model, the transient stable state of the multi-machine system model is improved based on the combined model.

[0216] To solve the technical problem of insufficient transient stability of power systems in the scenario of high - proportion wind power integration in the existing technology, the present invention proposes a method for improving the transient stability of a multi - machine system with wind power by combining superconducting magnetic energy storage. By constructing the mathematical models of superconducting magnetic energy storage and direct - drive wind power generation systems, a dynamic power compensation control strategy based on sliding - mode control is designed, and combined with the slope power recovery characteristics of the wind turbines, the optimal control of system frequency recovery and voltage stability is realized.

[0217] The following specifically illustrates the implementation manner of the present invention by examples.

[0218] In an embodiment of the present invention, a co - simulation model of a multi - machine system with wind power and SMES is constructed in the PSCAD / EMTDC platform, and three - phase short - circuit fault scenarios and wind power fluctuation scenarios are set to verify the improvement effect of SMES on the transient stability of the system.

[0219] Specifically, take the PSCAD simulation experiment of a three - machine nine - node system as an example.

[0220] 1. In the PSCAD simulation software, build a three - machine nine - node system model as shown in Figure 11 . Among them, G1 is a direct - drive wind power generation system established according to the parameters in Table 1, and SMES is installed at the common coupling point between the direct - drive wind power system and the step - up transformer according to the parameters in Table 2, and the parameters of other components are shown in Table 3. Set the simulation conditions as follows: When the simulation runs to 10 s, a three - phase short - circuit fault lasting for 0.5 s is applied to BUS1, causing the frequency to drop, and finally stabilizing again under the action of primary frequency modulation.

[0221] Table 1

[0222] Parameter Value Parameter Value Rated capacity of motor / MVA 5 DC capacitor / mF 5 Rated voltage of motor / kV 3.3 Rated voltage of DC side / kV 5.5 Rated frequency of motor / Hz 20 Current wind speed / m·s-1 9.50 Air density / kg·m3 1.22 Active power target value / p.u. 0.49 Radius of wind turbine blade / m 63 Reactive power target value / p.u. 0 Rated wind speed / m·s-1 11 Load reduction ratio / % 23.93 Natural inertia constant / s 2 Equivalent number of units 50 Filter inductor / mH 2 Grid voltage level 220

[0223] Table 2

[0224]

[0225] Table 3

[0226] Name Parameter Synchronous generator G2 Rated capacity 192 MVA, inertia constant 4.33 s, droop coefficient 20 Synchronous generator G3 Rated capacity 125 MVA, inertia constant 4.10 s, droop coefficient 8 Load Load1 Rated active power 125 MW, rated reactive power 50 Mvar Load Load2 Rated active power 90 MW, rated reactive power 30 Mvar Load Load3 Rated active power 100 MW, rated reactive power 35 Mvar

[0227] 2. Set two control experiments. The first group introduces a coordinated control strategy, and the second group does not introduce this strategy. The response characteristics of the two groups of experiments are shown in Figure 12 and Figure 13 respectively. The experimental results show that after adopting the coordinated active power recovery control strategy, the dynamic response performance of the system frequency is significantly improved. In the active power recovery stage, the coordinated control strategy increases the minimum value of the system frequency from 48.410 Hz without the strategy to 49.653 Hz, effectively suppressing the amplitude of frequency drop and making the frequency recovery process smoother.

[0228] Figure 14 This is a schematic structural diagram of a system 1400 for improving the transient stability of a multi-machine system by combining superconducting energy storage according to an embodiment of the present invention. As Figure 14 shown, the system 1400 for improving the transient stability of a multi-machine system by combining superconducting energy storage provided by the embodiment of the present invention includes: a multi-machine system model establishment unit 1401, a superconducting energy storage system model establishment unit 1402, a sliding mode control unit 1403, a configuration unit 1404, and a combined model establishment unit 1405.

[0229] Preferably, the multi-machine system model establishment unit 1401 is configured to establish a multi-machine system model including direct-drive wind power under a VSG control strategy; wherein, the grid-side converter of the multi-machine system model adopts a VSG control strategy.

[0230] Preferably, the multi-machine system model includes: a wind turbine model, a permanent magnet synchronous motor model, a back-to-back converter model including a machine-side converter and a grid-side converter, a DC capacitor model, a filter inductor model, a wind farm inertia response model, a machine-side converter overspeed load reduction control model, and a grid-side converter VSG control model.

[0231] Preferably, the superconducting energy storage system model establishment unit 1402 is configured to establish a superconducting energy storage system model.

[0232] Preferably, the superconducting energy storage system model establishment unit 1402 establishes a superconducting energy storage system model, including:

[0233] Establishing a current model on the AC side of the converter, an output voltage model on the AC side of the VSC, a dynamic power balance model between the AC and DC sides, a dynamic model of the VSC, a magnetization model of the superconducting magnet, a demagnetization model of the superconducting magnet, and a duty cycle model of the chopper pulse.

[0234] Preferably, the sliding mode control unit 1403 is configured to set a dynamic power compensation control strategy for the converter VSC in the superconducting energy storage system model based on sliding mode control.

[0235] Preferably, the sliding mode control unit 1403 sets a dynamic power compensation control strategy for the converter VSC in the superconducting energy storage system model based on sliding mode control, including:

[0236] Establishing a voltage outer loop control model designed based on a sliding mode surface:

[0237]

[0238] Establishing a sliding mode surface model:

[0239]

[0240] Establish the mathematical model of VSC voltage:

[0241]

[0242] Establish the output model of the voltage outer loop:

[0243]

[0244] Establish the complex power exponential reaching law model:

[0245]

[0246] Establish the sliding mode switching model:

[0247]

[0248] Establish the mathematical model of VSC current:

[0249]

[0250] Establish the control law model:

[0251]

[0252] Among them, L, R, and C represent the filter inductor value, the equivalent internal resistance of the inductor, the switching loss value, and the DC side capacitor value respectively; i d , i q are the currents on the grid side d and q axes respectively; u sd , u sq are the power supply voltages on the grid side d and q axes respectively; s d , s q are the switching functions on the d and q axes; S u (x), e u are the sliding mode surface model based on the DC side capacitor voltage and its intermediate variable respectively; S u′ (x) is the voltage outer loop sliding mode surface model; u dc , i dc are the voltage and current on the DC side of the chopper respectively; is the reference value of the voltage on the DC side of the chopper; λ is the feedback coefficient; s is the sliding mode surface; is the complex power exponential reaching law of the sliding mode motion; ε1, ε2 are the reaching coefficients; α, β are the high-order reaching coefficients; k is the exponential reaching coefficient; sgns is the sign function; s1, s2 are the intermediate variables of the sliding mode switching model; is the derivative of this intermediate variable; s d , s q are the switching functions on the d and q axes respectively; are the current reference values on the grid side d and q axes respectively; ω is the grid side voltage angular frequency; u td , utq They are the output voltages on the d-axis and q-axis of the VSC AC side respectively.

[0253] Preferably, the configuration unit 1404 is configured to configure the energy storage power and capacity of the superconducting energy storage system model.

[0254] Preferably, the configuration unit 1404 configures the energy storage power and capacity of the superconducting energy storage system model, including:

[0255] Establish a control rate model:

[0256] P SN = max{|P smes (t)|},

[0257] Establish an SOC model of SMES:

[0258]

[0259] Establish a charge / discharge amount model:

[0260]

[0261] Establish an energy storage constraint model:

[0262]

[0263] Among them, P smes (t) is the reference power of SMES at time t; P SN is the rated power of SMES; SOC(t) is the state of charge of SMES at time t; SOC0 is the initial state of charge of SMES; E SN is the rated capacity of SMES; E H (t) is the maximum cumulative charge; E L (t) is the maximum cumulative discharge of SMES; i max , i min and i0 are the maximum value, minimum value and initial value of the magnet current respectively.

[0264] Preferably, the joint model establishment unit 1405 is configured to construct a joint model including the multi-machine system model and the superconducting energy storage system model, so that the multi-machine system model can be in a transient stable state based on the joint model.

[0265] The system 1400 for improving the transient stability of a multi-machine system by joint superconducting energy storage in the embodiments of the present invention corresponds to the method 100 for improving the transient stability of a multi-machine system by joint superconducting energy storage in another embodiment of the present invention, which will not be elaborated here.

[0266] On another aspect of the present invention, the present invention provides a computer-readable storage medium, on which a computer program is stored, and when the program is executed by a processor, the steps of any one of the methods for improving the transient stability of a multi-machine system by combining superconducting energy storage are implemented.

[0267] On another aspect of the present invention, the present invention provides an electronic device, including:

[0268] The above-mentioned computer-readable storage medium; and

[0269] One or more processors for executing the program in the computer-readable storage medium.

[0270] The present invention has been described by referring to a few embodiments. However, as is well known to those skilled in the art, other embodiments equivalent to those disclosed above of the present invention equally fall within the scope of the present invention.

[0271] Generally, all terms used in the present invention are interpreted according to their ordinary meanings in the technical field, unless otherwise clearly defined therein. All references to "a / the [device, component, etc.]" are open to interpretation as at least one instance of the device, component, etc., unless otherwise clearly stated. The steps of any method disclosed herein need not be run in the exact order disclosed, unless clearly stated.

[0272] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0273] The present application is described with reference to the flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and the combination of flows and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, such that the instructions executed by the processor of the computer or other programmable data processing devices generate a device for implementing the functions specified in Figure 1 one process or multiple processes and / or blocks Figure 1 one block or multiple blocks.

[0274] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to operate in a particular manner, such that the instructions stored in the computer-readable memory produce a manufacture including an instruction device that implements the functions specified in one or more of the processes Figure 1 one or more of the processes and / or blocks Figure 1 specified in the blocks or blocks.

[0275] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process, whereby the instructions executed on the computer or other programmable apparatus provide steps for implementing the functions specified in one or more of the processes Figure 1 one or more of the processes and / or blocks Figure 1 specified in the blocks or blocks.

[0276] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them. Although the present invention has been described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that: modifications or equivalent replacements can still be made to the specific embodiments of the present invention. Any modifications or equivalent replacements that do not depart from the spirit and scope of the present invention shall be covered by the protection scope of the present invention.

Claims

1. A method for improving the transient stability of a multi-machine system by combining superconducting energy storage, characterized in that The method includes: Establishing a multi-machine system model including direct-drive wind power under the VSG control strategy; wherein, the grid-side converter of the multi-machine system model adopts the VSG control strategy; Establishing a superconducting energy storage system model; Based on sliding mode control, setting a dynamic power compensation control strategy for the converter VSC in the superconducting energy storage system model; Configuring the energy storage power and capacity of the superconducting energy storage system model; Constructing a combined model including the multi-machine system model and the superconducting energy storage system model, so that the multi-machine system model can be in a transient stable state based on the combined model.

2. The method according to claim 1, characterized in that, The multi-machine system model includes: a wind turbine model, a permanent magnet synchronous motor model, a back-to-back converter model including a machine-side converter and a grid-side converter, a DC capacitor model, a filter inductor model, a wind farm inertia response model, a machine-side converter overspeed load shedding control model, and a grid-side converter VSG control model.

3. The method according to claim 1, characterized in that, The establishing of the superconducting energy storage system model includes: Establishing a current model of the AC side of the converter, an output voltage model of the VSC AC side, a dynamic power balance model of the AC / DC sides, a dynamic model of the VSC, a magnetization model of the superconducting magnet, a demagnetization model of the superconducting magnet, and a duty cycle model of the chopper pulse.

4. The method according to claim 1, characterized in that The setting of the dynamic power compensation control strategy for the converter VSC in the superconducting energy storage system model based on sliding mode control includes: Establishing a voltage outer loop control model designed based on a sliding surface: Establishing a sliding surface model: Establishing a VSC voltage mathematical model: Establishing a voltage outer loop output model: Establishing a complex power exponential reaching law model: Establishing a sliding mode switching model: Establishing a VSC current mathematical model: Establishing a control law model: Among them, L, R, and C respectively represent the filter inductance value, the equivalent internal resistance of the inductor and the switching loss value, and the DC-side capacitor value; i d 、i q are the currents on the grid-side d and q axes respectively; u sd 、u sq are the power supply voltages on the grid-side d and q axes respectively; s d 、s q are the switching functions on the d and q axes; S u (x), e u are respectively the sliding mode surface model based on the DC-side capacitor voltage and its intermediate variable; S u′ (x) is the voltage outer-loop sliding mode surface model; u dc 、i dc are respectively the voltage and current on the DC side of the chopper; is the reference value of the voltage on the DC side of the chopper; λ is the feedback coefficient; s is the sliding mode surface; is the complex power exponential reaching law of the sliding mode motion; ε1, ε2 are the reaching coefficients; α, β are the high-order reaching coefficients; k is the exponential reaching coefficient; sgns is the sign function; s1, s2 are the intermediate variables of the sliding mode switching model; is the derivative of this intermediate variable; s d 、s q are the switching functions on the d and q axes respectively; are the current reference values on the grid-side d and q axes respectively; ω is the grid-side voltage angular frequency; u td 、u tq are the output voltages on the VSC AC-side d and q axes respectively.

5. The method according to claim 1, wherein The configuring of the energy storage power and capacity of the superconducting energy storage system model includes: Establishing a control law model: P SN = max{|P smes (t)|}, Establishing an SOC model of the SMES: Establishing a charge / discharge amount model: Establishing an energy storage constraint model: Among them, P smes (t) is the reference power of the SMES at time t; P SN is the rated power of the SMES; SOC(t) is the state of charge of the SMES at time t; SOC0 is the initial state of charge of the SMES; E SN is the rated capacity of the SMES; E H (t) is the maximum cumulative charge; E L (t) is the maximum cumulative discharge of the SMES; i max , i min and i0 are the maximum value, minimum value and initial value of the magnet current respectively.

6. A system for improving the transient stability of a multi-machine system by combining superconducting energy storage, characterized in that, The system includes: A multi-machine system model establishing unit, used for establishing a multi-machine system model including direct-drive wind power under the VSG control strategy; wherein, the grid-side converter of the multi-machine system model adopts the VSG control strategy; A superconducting energy storage system model establishing unit, used for establishing a superconducting energy storage system model; A sliding mode control unit, used for setting a dynamic power compensation control strategy for the converter VSC in the superconducting energy storage system model based on sliding mode control; A configuration unit, used for configuring the energy storage power and capacity of the superconducting energy storage system model; A combined model establishing unit, used for constructing a combined model including the multi-machine system model and the superconducting energy storage system model, so that the multi-machine system model can be in a transient stable state based on the combined model.

7. The system according to claim 6, characterized in that, The multi-machine system model includes: a wind turbine model, a permanent magnet synchronous motor model, a back-to-back converter model including a machine-side converter and a grid-side converter, a DC capacitor model, a filter inductor model, a wind farm inertia response model, a machine-side converter overspeed load shedding control model, and a grid-side converter VSG control model.

8. The system according to claim 6, characterized in that, The superconducting energy storage system model establishing unit establishes a superconducting energy storage system model, including: Establish the current model of the AC side of the converter, the output voltage model of the AC side of the VSC, the dynamic power balance model of the AC and DC sides, the dynamic model of the VSC, the magnetization model of the superconducting magnet, the demagnetization model of the superconducting magnet, and the duty cycle model of the chopper pulse.

9. The system according to claim 6, wherein The sliding mode control unit sets the dynamic power compensation control strategy of the VSC in the superconducting energy storage system model based on sliding mode control, including: Establish a voltage outer loop control model based on the design of the sliding mode surface: Establish a sliding mode surface model: Establish the VSC voltage mathematical model: Establish the voltage outer loop output model: Establish a complex power exponential reaching law model: Establish a sliding mode switching model: Establish the VSC current mathematical model: Establish a control law model: Among them, L, R, and C respectively represent the filter inductance value, the equivalent internal resistance of the inductor and the switching loss value, and the DC-side capacitor value; i d and i q are the currents on the grid-side d and q axes respectively; u sd and u sq are the supply voltages on the grid-side d and q axes respectively; s d and s q are the switching functions on the d and q axes; S u (x) and e u are the sliding mode surface model based on the DC-side capacitor voltage and its intermediate variable respectively; S u′ (x) is the voltage outer-loop sliding mode surface model; u dc and i dc are the voltage and current on the DC side of the chopper respectively; is the reference value of the voltage on the DC side of the chopper; λ is the feedback coefficient; s is the sliding mode surface; is the complex power exponential reaching law of the sliding mode motion; ε1, ε2 are the reaching coefficients; α, β are the high-order reaching coefficients; k is the exponential reaching coefficient; sgns is the sign function; s1, s2 are the intermediate variables of the sliding mode switching model; is the derivative of this intermediate variable; s d and s q are the switching functions on the d and q axes respectively; are the current reference values on the grid-side d and q axes respectively; ω is the angular frequency of the grid-side voltage; u td and u tq are the output voltages on the VSC AC-side d and q axes respectively.

10. The system according to claim 6, wherein The configuration unit configures the energy storage power and capacity of the superconducting energy storage system model, including: Establish a control law model: P SN = max{|P smes (t)|}, Establish the SOC model of the SMES: Establish a charge / discharge amount model: Establish an energy storage constraint model: Among them, P smes (t) is the reference power of the SMES at time t; P SN is the rated power of the SMES; SOC(t) is the state of charge of the SMES at time t; SOC0 is the initial state of charge of the SMES; E SN is the rated capacity of the SMES; E H (t) is the maximum cumulative charge; E L (t) is the maximum cumulative discharge of the SMES; i max , i min and i0 are the maximum value, minimum value and initial value of the magnet current respectively.

11. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by a processor, it implements the steps of the method according to any one of claims 1-5.

12. An electronic device, characterized in that, Including: The computer-readable storage medium described in claim 11; And One or more processors for executing the program in the computer-readable storage medium.

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