Improved sliding-mode active-disturbance-rejection control method for grid-forming type photovoltaic hybrid energy storage converter

Abstract

The invention discloses an improved sliding-mode active-disturbance-rejection control method for a network construction type photovoltaic hybrid energy storage converter, and provides an improved sliding-mode active-disturbance-rejection control strategy based on a quasi-continuous algorithm on the basis of a virtual synchronous generator (VSG) technology, the VSG is often matched with a voltage and current double-closed-loop strategy, a voltage outer loop adopts PI control, a reference value is provided for a current inner loop, and the current inner loop adopts PI control. A high-order super-spiral sliding mode observer (HO-STSMO) is adopted in a current inner ring, so that the response speed and the tracking precision are better; meanwhile, a double-sliding-mode switching control law form is adopted, a quasi-continuous integral terminal sliding mode controller (QC-ITSMC) is introduced, and an improved index reaching law is designed to smooth a system control signal and improve the robustness of the system; according to the control method, power grid power fluctuation is effectively suppressed, the performance of the photovoltaic hybrid energy storage converter is improved, the bus voltage is kept stable, and the system operation stability is improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of power electronics, and in particular relates to an improved sliding mode active disturbance rejection control method for a grid-connected photovoltaic hybrid energy storage converter. Background Art

[0002] With the gradual phase-out of synchronous generators, modern power systems are experiencing a shift from high-inertia, strong grids dominated by generators to low-inertia, weak grids dominated by power electronics. This has led to deficiencies in power systems in terms of interference immunity, frequency regulation, and voltage and frequency regulation. The intermittent and random nature of wind and photovoltaic power generation poses a significant challenge in new power systems integrating a high proportion of clean energy. Against this backdrop, grid-connected energy storage converters based on virtual synchronous generators (VSGs) have become a research hotspot. By simulating the operating characteristics of synchronous generators, they provide stable voltage and frequency support for the grid, enhancing power system reliability.

[0003] Currently, research on grid-forming VSG algorithms has spawned two main research directions: optimizing VSG parameter tuning methods and improving converter control algorithms to enhance the performance of grid-forming energy storage converters. In photovoltaic hybrid energy storage systems, since the photovoltaic storage system must operate synchronously with the external grid, the VSG's regulation capability is limited when the external grid frequency fluctuates significantly. Large frequency fluctuations can cause system instability, which in turn affects the quality of power output and the overall operation of the system. Furthermore, the continuous charging and discharging of the battery packs in the energy storage module can cause fluctuations in the DC bus voltage, affecting the normal operation of the system. Therefore, maintaining bus voltage stability is crucial.

[0004] Photovoltaic arrays, energy storage units, DC / DC converters and converters are the main components of photovoltaic hybrid energy storage systems, which are coupled to the AC power grid through the DC bus. Due to the nonlinearity, multivariable, and strong coupling characteristics of photovoltaic storage systems, traditional linear control strategies are difficult to achieve ideal control performance. Therefore, scholars have conducted in-depth research on the control strategy of grid-type converters. Among the many schemes, the composite control strategy has complex parameter setting and large algorithm calculation amount. The sliding mode control (SMC) has strong robustness to system uncertainties and external disturbances due to its simple physical implementation. It is especially suitable for nonlinear systems and is used in hypersonic aircraft, permanent magnet synchronous motors, and UAV trajectory tracking.

[14] However, in SMC, due to the high-frequency switching of the control signal, the output signal will oscillate. How to properly deal with the chattering phenomenon in SMC is currently a problem that needs to be solved. Summary of the Invention

[0005] The purpose of the present invention is to provide an improved sliding mode active disturbance rejection control method for a grid-connected photovoltaic hybrid energy storage converter, which solves the chattering problem in traditional SMC.

[0006] The technical solution adopted by the present invention is to improve the sliding mode active disturbance rejection control method of the grid-connected photovoltaic hybrid energy storage converter, which is specifically implemented according to the following steps: Step 1: Establish the mathematical model of the converter and the state equation of the front-stage DC converter based on the photovoltaic hybrid energy storage system; Step 2: Network-based VSG control design By embedding the control algorithm into the mathematical model of the synchronous machine, the stationary power electronic device can simulate the behavior of the rotating machine. Based on this, the active and reactive power can be controlled by adjusting the output voltage and current of the converter. Step 2.1: P - f Speed ​​controller design; Step 2.2: Q - E Excitation controller design; Step 3: Converter control design; Step 3.1: Design of high-order super-helical sliding mode observer; Step 3.2: Converter Controller Design Step 4: Pre-stage DC converter control design.

[0007] The present invention is also characterized in that: Step 1 is as follows: The photovoltaic hybrid energy storage system includes a photovoltaic array, an energy storage unit, a bidirectional DC / DC converter, an inverter, an AC load and a distribution network. The energy storage unit includes a battery and a supercapacitor. The battery and supercapacitor are connected to the bidirectional DC / DC converter. The bidirectional DC / DC converter is connected to the subsequent converter, the distribution network and the AC load in sequence through the DC bus. The photovoltaic array is connected to the DC bus through the Boost boost circuit. A filtering link is set between the subsequent converter and the distribution network. The Boost boost circuit includes a set of switching tubes. T p1 、 T p2 The bidirectional DC / DC converter connected to the battery includes a switch tube T b1 、 T b2 and inductance L b The bidirectional DC / DC converter connected to the supercapacitor includes a switch tube T c1 、 T c2 and inductance Lc , T b1 、 T b2 and T c1 、 T c2 There are two pairs of complementary conducting switch tubes. The converter includes 6 switch tubes in the upper and lower bridge arms. s 1~ s 6; According to Kirchhoff's law, the mathematical model of the converter in the abc three-phase stationary coordinate system is: (1) In formula (1): u Ca 、u Cb 、u Cc For AC capacitance measurement C Voltage across both ends; s ka 、s kb 、s kc is the converter three-phase bridge arm switch control signal, u a 、 u b 、 u c is the three-phase voltage on the AC side of the converter; i a 、i b 、i c is the three-phase current after converter filtering, i sa 、 i sb 、 i sc is the three-phase current on the AC side of the converter, L 、 C For filter inductors and capacitors, R is the equivalent resistance of the circuit, e a 、 e b 、 e c is the AC grid voltage, i s is the DC side output current of the converter, i C is the DC bus current; Perform Park transformation on equation (1), and the mathematical model of the converter in the dq rotating coordinate system is: (2) In formula (2): ω is the angular frequency of the grid voltage; e d 、i d 、u Cd 、s d is the d-axis grid voltage, current, capacitor voltage and switching function, e q 、i q 、u Cq 、s q are q-axis grid voltage, current, capacitor voltage and switching function respectively; The state equation of the front-stage DC / DC converter is as follows: (3) In formula (3): D 1. D 2 are switching tubes T b1 、 T c1 On-duty cycle, D 3 is the switch tube T p2 Shutdown duty cycle, u bat 、 u suc 、 u pv They are the output voltages of the battery pack, supercapacitor, and photovoltaic array respectively. i bat 、 i suc 、 i pv They are the output currents of the battery pack, supercapacitor and photovoltaic array respectively. u dc is the DC bus voltage.

[0008] Step 2.1 is as follows: According to Newton's second law, the mechanical equation of the virtual synchronous generator, that is, the rotor motion equation, can be expressed as follows: (4) In formula (4): J is the moment of inertia; D is the damping coefficient; P m 、 Pe is mechanical power and electromagnetic power; 、 are the reference angular velocity and the grid synchronization angular velocity; is the power angle; In order to simulate the frequency regulation characteristics of synchronous generators, a speed regulator is applied in VSG control, namely P - f The droop characteristics are as follows: (5) Where: P ref is the reference active power; k f for P - f droop coefficient; Substitute equation (5) into equation (4) and perform Laplace transform: (6) According to formula (6), the phase reference information of the VSG terminal voltage is obtained ω* .

[0009] Step 2.2 is as follows: The synchronous generator adjusts the output reactive power and terminal voltage by adjusting the excitation. Similarly, the virtual potential of the virtual synchronous machine can be controlled E m The amplitude and phase of the reactive power are used to adjust the output reactive power to ensure the stability of the terminal voltage. Therefore, a voltage deviation is introduced into the VSG reactive power loop to adjust the system reactive power. The VSG reactive power and voltage droop characteristics are shown in the following formula: (7) In formula (7): Q ref is the reactive reference; U n is the effective value of the terminal voltage; U s is the actual output voltage of VSG; k q for QE droop coefficient; From formula (7), we know that by adjusting the VSG output voltage amplitude and phase, the system reactive power command is tracked to provide reactive power support for the photovoltaic hybrid energy storage system. E m The output will Q * and electromagnetic reactive power Q e Compare and integrate, and finally get the virtual potential E mThe amplitude of .

[0010] Step 3.1 is as follows: Suppose the following second-order controlled object: (8) In formula (8): x is the system status, u ( t ) is the control input, b is the control quantity gain, f ( x , u ) are all uncertainties and unknown disturbances in the system; make , and expand it to a first-order state, then the above second-order system is expanded to the following form: (9) In formula (9): x 1 is the system status, x 2 is the system state differential, x 3 is the total disturbance of the system.

[0011] For the system (8), the following high-order super-spiral sliding mode observer HO-STSMO is constructed: (10) In formula (10): e 1 is the observation error; z 1. z 2. z 3 for x 1. x 2. f estimated value; 、 、 is the gain coefficient; because In the presence of discontinuity, the discontinuous switching term is replaced by a hyperbolic function. Based on the feedforward theory, the super-helical sliding mode observer is improved as follows: First, transform Equation (2) to obtain the state variables d and q axis currents i sd 、 i sq The first-order differential form is as follows: (11) The d-axis and q-axis current coupling terms and the unmodeled part are regarded as lumped disturbances, respectively. f d 、 f qExpressed as follows, the derivative of Equation (11) is converted into the second-order ADRC paradigm as follows: (12) In formula (12): b o for b Estimated value, f d 、 f q As shown below: (13) Take the feedforward error signal for the above system , i ref is the current reference value, find its second-order derivative and substitute equation (12) into it: (14) Select state variables , , , then the system shown in formula (12) is transformed into: (15) For the feedforward error system shown in Equation (15), the lumped disturbances of the d and q axes are f d 、 f q Expand to new state variables z d3 、 z q3 , then design the d-axis and q-axis observers respectively; The designs of the d-axis and q-axis high-order super-helical sliding mode observers are as follows: (16) (17) In formula (16) to formula (17): e d1 、 e q1 is the state observation error; z d1 、 z d2 、 z d3 and z q1 、 z q2 、 z q3 They are x d1 、 x d2、 f d and x q1 、 x q2 、 f q estimated value of; φ d1 、 φ d2 、 φ d3 and φ q1 、 φ q2 、 φ q3 are the d-axis and q-axis observer gains respectively.

[0012] In step 3.1, the hyperbolic function F( e i ) is shown in the following formula: (18).

[0013] Step 3.2 is as follows: An improved second-order quasi-continuous integral terminal sliding mode controller (IQC-ITSMC) is designed. The specific process is as follows: definition 、 is the system state deviation of the d and q axes, as shown below: (19) According to formula (19), the following integral terminal sliding surface is designed: (20) In formula (20): , ; α , β is the sliding surface adaptive control parameter, and its expression is as follows: (twenty one) In formula (21): 、 is the adaptive gain, both greater than 0; Differentiate equation (20) and substitute equation (15) into it to obtain: (twenty two) (twenty three) Since the system converges in finite time, according to the equivalent control theory, let , we get the system equivalent control law of d and q axes: (twenty four); As shown in formula (23), the sliding surface The control quantity appears for the first time in the second-order differential s , so the relative order of the system is 2. In order to generate a continuous control signal, a second-order quasi-continuous algorithm is introduced as the sliding mode switching control law, which is designed as follows: (25) In formula (25): l d 、 l q are the proportional coefficients of the d-axis and q-axis switching controllers, is a saturation function, as shown below: (26) In formula (26): is the boundary layer thickness; The improved exponential reaching law is designed as the second-stage switching controller of the sliding mode motion as shown below: (27) In formula (27): 、 is the reaching law gain coefficient, all greater than 0; In summary, the system switches the controller s sw , the design is as follows: (28) In formula (28): Switch controller for d axis, 、 Switching control law for the d-axis Switch controller for the q axis, is the q-axis switching control law.

[0014] In formula (28): γ is the switching term, which ensures the switching control law s sw1 and s sw2 The working state is switched under the following conditions: (29) In formula (29): is a positive constant; Combining equations (24) and (28), we can obtain the second-order quasi-continuous sliding mode control law of the photovoltaic hybrid energy storage converter system as follows: (30).

[0015] Step 4 is as follows: The bus voltage constant control is adopted for the front-stage DC converter, i.e. the bidirectional DC / DC converter. The design process is as follows: Derivative equation (3) is converted into a second-order ADRC form: (31) In formula (31): b sc is the control quantity gain, u 2 is the converter switch control signal, f sc is the total disturbance inside and outside the system, as shown in the following formula: (32) Select state quantity , ,make , and expand it into a first-order state, then design the following observer: (33) In formula (33): e 2 is the observation bias; z 1. z 2. z 3 for x 1. x 2. f sc estimated value; φ sc1 、 φ sc2 、 φ sc3 is the gain coefficient; Select the following linear sliding surfaces: (34) In formula (34): is the sliding surface coefficient, and satisfies ; Defining systematic error , and the improved exponential reaching law is selected as the switching control law, then the feedback control law is as follows: (35) In formula (35): u 2 is the switch tube T c1 、 T c2 Control signal.

[0016] The beneficial effects of the present invention are: The improved sliding mode active disturbance rejection control method of the grid-type photovoltaic hybrid energy storage converter of the present invention is based on the virtual synchronous generator (VSG) technology and proposes an improved sliding mode active disturbance rejection control strategy based on the quasi-continuous algorithm. The VSG is often coordinated with the voltage and current dual closed-loop strategy. The voltage outer loop adopts PI control to provide a reference value for the current inner loop. The current inner loop adopts a high-order super-spiral sliding mode observer (HO-STSMO) with better response speed and tracking accuracy. At the same time, a dual sliding mode switching control law is adopted, a quasi-continuous integral terminal sliding mode controller (QC-ITSMC) is introduced, and an improved exponential reaching law is designed to smooth the system control signal and improve the system robustness. The control method of the present invention effectively suppresses grid power fluctuations, improves the performance of the photovoltaic hybrid energy storage converter, maintains bus voltage stability, and improves system operation stability. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 This is the main circuit topology diagram of the photovoltaic hybrid energy storage converter; Figure 2 yes P - f Speed ​​control block diagram; Figure 3 yes Q - E Excitation control block diagram; Figure 4 is the hyperbolic function F( e i ) and sgn( x ) comparison chart; Figure 5 This is a comparison chart of sliding mode chattering and tracking error; Figure 6 This is the working principle diagram of the improved quasi-continuous integral terminal sliding mode controller; Figure 7 This is the current inner loop control block diagram; Figure 8 This is the control structure diagram of the photovoltaic hybrid energy storage system; Figure 9 is the photovoltaic power output power diagram; FIG10 is a diagram showing the DC bus voltage response under photovoltaic fluctuations, wherein FIG10(a) is a diagram showing the DC bus voltage response, FIG10(b) is a diagram showing the transient process at point A in FIG10(a), FIG10(c) is a diagram showing the transient process at point B in FIG10(a), and FIG10(d) is a diagram showing the transient process at point C in FIG10(a); FIG11 is a diagram of the transient response of the system when the active power instruction suddenly changes, wherein FIG11( a ) is a diagram of the transient response of the active power, and FIG11( b ) is a diagram of the transient response of the bus voltage. DETAILED DESCRIPTION

[0018] The present invention will be described in detail below with reference to the accompanying drawings and specific embodiments.

[0019] Example 1 This embodiment provides an improved sliding mode active disturbance rejection control method for a grid-connected photovoltaic hybrid energy storage converter, which is specifically implemented according to the following steps: Step 1: Establish the mathematical model of the converter and the state equation of the front-stage DC converter based on the photovoltaic hybrid energy storage system; Step 2: Network-based VSG control design By embedding the control algorithm into the mathematical model of the synchronous machine, the stationary power electronic device can simulate the behavior of the rotating machine. Based on this, the active and reactive power can be controlled by adjusting the output voltage and current of the converter. Step 2.1: P - f Speed ​​controller design; Step 2.2: Q - E Excitation controller design; Step 3: Converter control design; VSG control usually adopts a voltage and current dual closed-loop control strategy. The voltage outer loop is used to control the amplitude and phase of the output voltage to maintain grid voltage stability; the current inner loop is used to quickly adjust the output current to achieve precise control of active and reactive power. Therefore, the current loop is designed; Step 3.1: Design of high-order super-helical sliding mode observer; Step 3.2: Converter controller design; Step 4: Pre-stage DC converter control design.

[0020] Example 2 This embodiment provides an improved sliding mode active disturbance rejection control method for a grid-connected photovoltaic hybrid energy storage converter. Based on embodiment 1, step 1 is specifically as follows: PV-HPCS structure Figure 1 As shown, the photovoltaic hybrid energy storage system includes a photovoltaic array, an energy storage unit, a bidirectional DC / DC converter, an inverter, an AC load and a distribution network. The energy storage unit includes a battery and a supercapacitor. The battery and the supercapacitor are connected to the bidirectional DC / DC converter. The bidirectional DC / DC converter is connected to the subsequent inverter, the distribution network and the AC load in sequence through the DC bus. The photovoltaic array is connected to the DC bus through the Boost boost circuit to increase the output voltage to the required level to meet the needs of subsequent circuits and loads. A filtering link is set between the subsequent inverter and the distribution network. The Boost boost circuit includes a set of switching tubes. T p1 、 T p2The bidirectional DC / DC converter connected to the battery includes a switch tube T b1 、 T b2 and inductance L b The bidirectional DC / DC converter connected to the supercapacitor includes a switch tube T c1 、 T c2 and inductance L c , T b1 、 T b2 and T c1 、 T c2 There are two pairs of complementary conducting switch tubes. The converter includes 6 switch tubes in the upper and lower bridge arms. s 1~ s 6. Figure 1 middle i o is the converter input current; it is assumed that the grid voltage waveform is symmetrical and undistorted; Depend on Figure 1 According to Kirchhoff's law, the mathematical model of the converter in the abc three-phase stationary coordinate system is: (1) In formula (1): u Ca 、u Cb 、u Cc For AC capacitance measurement C Voltage across both ends; s ka 、s kb 、s kc is the converter three-phase bridge arm switch control signal, u a 、 u b 、 u c is the three-phase voltage on the AC side of the converter; i a 、i b 、i c is the three-phase current after converter filtering, i sa 、 i sb 、 isc is the three-phase current on the AC side of the converter, L 、 C For filter inductors and capacitors, R is the equivalent resistance of the circuit, e a 、 e b 、 e c is the AC grid voltage, i s is the DC side output current of the converter, i C is the DC bus current; Perform Park transformation on equation (1), and the mathematical model of the converter in the dq rotating coordinate system is: (2) In formula (2): ω is the angular frequency of the grid voltage; e d 、i d 、u Cd 、s d is the d-axis grid voltage, current, capacitor voltage and switching function, e q 、i q 、u Cq 、s q are q-axis grid voltage, current, capacitor voltage and switching function respectively; The state equation of the front-stage DC / DC converter is as follows: (3) In formula (3): D 1. D 2 are switching tubes T b1 、 T c1 On duty cycle, D 3 is the switch tube T p2 Shutdown duty cycle, u bat 、 u suc 、 u pv They are the output voltages of the battery pack, supercapacitor, and photovoltaic array respectively. i bat 、 i suc 、 ipv They are the output currents of the battery pack, supercapacitor and photovoltaic array respectively. u dc is the DC bus voltage.

[0021] As can be seen from the above model, PV-HPCS has multivariable, nonlinear, and strongly coupled characteristics. Traditional linear control is difficult to achieve ideal control effects. Therefore, this embodiment proposes an improved sliding mode active disturbance rejection control strategy to improve the operating performance of the photovoltaic storage converter.

[0022] Example 3 This embodiment provides an improved sliding mode active disturbance rejection control method for a grid-connected photovoltaic hybrid energy storage converter. Based on the embodiment 1-2, step 2.1 is specifically as follows: According to Newton's second law, the mechanical equation of the virtual synchronous generator, that is, the rotor motion equation, can be expressed as follows: (4) In formula (4): J is the moment of inertia; D is the damping coefficient; P m 、 P e is mechanical power and electromagnetic power; 、 are the reference angular velocity and the grid synchronization angular velocity; is the power angle; In order to simulate the frequency regulation characteristics of synchronous generators, a speed regulator is applied in VSG control, namely P - f The droop characteristics are as follows: (5) Where: P ref is the reference active power; k f for P - f droop coefficient; Substitute equation (5) into equation (4) and perform Laplace transform: (6) According to formula (6), the phase reference information of the VSG terminal voltage is obtained ω* ,thus, Pf The speed control block diagram is as follows Figure 2 shown.

[0023] Example 4 This embodiment provides an improved sliding mode active disturbance rejection control method for a grid-connected photovoltaic hybrid energy storage converter. Based on embodiments 1-3, step 2.2 is specifically as follows: The synchronous generator adjusts the output reactive power and terminal voltage by adjusting the excitation. Similarly, the virtual potential of the virtual synchronous machine can be controlled E m The amplitude and phase of the reactive power are used to adjust the output reactive power to ensure the stability of the terminal voltage. Therefore, a voltage deviation is introduced into the VSG reactive power loop to adjust the system reactive power. The VSG reactive power and voltage droop characteristics are shown in the following formula: (7) In formula (7): Q ref is the reactive reference; U n is the effective value of the terminal voltage; U s is the actual output voltage of VSG; k q for QE droop coefficient; From formula (7), we know that by adjusting the VSG output voltage amplitude and phase, the system reactive power command is tracked to provide reactive power support for the photovoltaic hybrid energy storage system. E m The output will Q * and electromagnetic reactive power Q e Compare and integrate, and finally get the virtual potential E m The amplitude of the control block diagram is as follows Figure 3 shown.

[0024] Example 5 This embodiment provides an improved sliding mode active disturbance rejection control method for a grid-connected photovoltaic hybrid energy storage converter. Based on embodiments 1-4, step 3.1 is to improve the accuracy and speed of the observer's observation of system state quantities and lumped disturbances. Based on the feedforward concept, a high-order super-spiral sliding mode observer is improved and designed. Specifically, Suppose the following second-order controlled object: (8) In formula (8): x is the system status, u ( t ) is the control input, b is the control quantity gain, f ( x , u ) are all uncertainties and unknown disturbances in the system; make , and expand it to a first-order state, then the above second-order system is expanded to the following form: (9) In formula (9): x 1 is the system status, x 2 is the system state differential, x 3 is the total disturbance of the system.

[0025] For the system (8), the following high-order super-spiral sliding mode observer HO-STSMO is constructed: (10) In formula (10): e 1 is the observation error; z 1. z 2. z 3 for x 1. x 2. f estimated value; 、 、 is the gain coefficient; because The existence of discontinuities can easily lead to chattering. To improve the performance of the observer, the discontinuous switching term is replaced by a hyperbolic function. Based on the feedforward theory, the super-helical sliding mode observer is improved as follows: First, transform Equation (2) to obtain the state variables d and q axis currents i sd 、 i sq The first-order differential form is as follows: (11) Due to the actual engineering b The value is generally unknown. To simplify the controller design, the d-axis and q-axis current coupling terms and the unmodeled part are regarded as lumped disturbances and are expressed as f d 、 f q Expressed as follows, the derivative of Equation (11) is converted into the second-order ADRC paradigm as follows: (12) In formula (12): b o for b Estimated value, f d 、 f q As shown below: (13) For the above system, take the feedforward error signal , i refis the current reference value, find its second-order derivative and substitute equation (12) into it: (14) Select state variables , , , then the system shown in formula (12) is transformed into: (15) For the feedforward error system shown in Equation (15), the lumped disturbances of the d and q axes are f d 、 f q Expand to new state variables z d3 、 z q3 , then design the d-axis and q-axis observers respectively; The designs of the d-axis and q-axis high-order super-helical sliding mode observers are as follows: (16) (17) In formula (16) to formula (17): e d1 、 e q1 is the state observation error; z d1 、 z d2 、 z d3 and z q1 、 z q2 、 z q3 They are x d1 、 x d2 、 f d and x q1 、 x q2 、 f q estimated value of; φ d1 、 φ d2 、 φ d3 and φ q1 、 φ q2 、 φ q3are the d-axis and q-axis observer gains respectively; Hyperbolic function F( e i ) is shown in the following formula: (18).

[0026] like Figure 4 , switching function F( e i ) is continuous and smooth, and the oscillation amplitude of the sliding surface approaching zero is reduced, which effectively weakens the chattering.

[0027] Example 6 This embodiment provides an improved sliding mode anti-disturbance control method for a grid-connected photovoltaic hybrid energy storage converter. Based on embodiments 1-5, step 3.2 uses a quasi-continuous algorithm as a high-order sliding mode algorithm that can generate a continuous control signal. ITSMC has a fast convergence speed and can ensure that the system converges in a finite time. In order to suppress the chattering phenomenon and improve the robustness of the system, this paper combines the ideas of the two to design an improved second-order quasi-continuous integral terminal sliding mode controller (IQC-ITSMC), specifically, An improved second-order quasi-continuous integral terminal sliding mode controller (IQC-ITSMC) is designed. The specific process is as follows: definition 、 is the system state deviation of the d and q axes, as shown below: (19) According to formula (19), the following integral terminal sliding surface is designed: (20) In formula (20): , ; α , β is the sliding surface adaptive control parameter, and its expression is as follows: (twenty one) In formula (21): 、 is the adaptive gain, both greater than 0; Differentiate equation (20) and substitute equation (15) into it to obtain: (twenty two) (twenty three) Since the system converges in finite time, according to the equivalent control theory, let , we get the system equivalent control law of d and q axes: (twenty four); As shown in formula (23), the sliding surface The control quantity appears for the first time in the second-order differential s , so the relative order of the system is 2. In order to generate a continuous control signal, a second-order quasi-continuous algorithm is introduced as the sliding mode switching control law, which is designed as follows: (25) In formula (25): l d 、 l q are the proportional coefficients of the d-axis and q-axis switching controllers, is a saturation function, as shown below: (26) In formula (26): is the boundary layer thickness; It can be seen from formula (25) that when the system is far away from the sliding mode surface, the above algorithm can provide a continuous control signal to act on the system to achieve chatter-free control; but when the sliding mode surface is 0, the algorithm has a zero point, which causes the system to have large chattering. Therefore, this paper designs an improved exponential reaching law as the second stage switching controller of sliding mode motion.

[0028] The traditional exponential convergence law is , by adjusting The size of can balance the approach speed and chattering to a certain extent, but when When the value is small, the dynamic performance of the system cannot be guaranteed, resulting in slow system approach speed and long convergence time; when When the value is set to a large value, the system converges to the sliding surface too quickly, which may cause chattering. In view of the shortcomings of the traditional exponential reaching law, an improved exponential reaching law is designed as the second-stage switching controller of the sliding mode motion, as shown below: (27) In formula (27): 、 is the reaching law gain coefficient, all greater than 0; In order to verify the feasibility and superiority of the improved exponential convergence law of this embodiment, the sliding surface parameters are kept α 、 β , exponential gain coefficient The tracking errors and sliding surface chattering of the two are consistent. Figure 5 ,according to Figure 5 From formula (26), we can get that when the system motion state is far away from the sliding surface, that is, θ →∞, f ( θ )→∞, the system convergence speed is accelerated; when θ →0 o'clock, f ( θ )→1, constant speed gain coefficient → Compared with the traditional exponential reaching law, the convergence speed of the system near the sliding surface is significantly reduced. Therefore, the above improved exponential reaching law can effectively improve the dynamic performance of the system, ensure the convergence speed of the system, and further suppress the system chattering phenomenon; In summary, the system switches the controller s sw , the design is as follows: (28) In formula (28): Switch controller for d axis, 、 Switching control law for the d-axis Switch controller for the q axis, is the q-axis switching control law. γ is the switching term, which ensures the switching control law s sw1 and s sw2 The working state is switched under the following conditions: (29) In formula (29): is a positive constant; Switch Controller s sw1 and s sw2 Working mechanism Figure 6 ; Combining equations (24) and (28), we can obtain the second-order quasi-continuous sliding mode control law of the photovoltaic hybrid energy storage converter system as follows: (30).

[0029] In summary, the current inner loop control structure can be obtained as follows: Figure 7 shown.

[0030] Example 7 This embodiment provides an improved sliding mode active disturbance rejection control method for a grid-connected photovoltaic hybrid energy storage converter. Based on embodiments 1-6, step 4 is specifically as follows: To smooth out high- and low-frequency power fluctuations and maintain bus voltage stability, effective control of the DC / DC converters preceding the photovoltaic unit and energy storage module is crucial. This paper employs the perturbation-observation method within the MPPT algorithm to apply a perturbation to the photovoltaic output voltage, dynamically adjusting the perturbation direction to guide the operation of the boost converter. To reduce charging and discharging energy consumption and improve the efficiency of the photovoltaic hybrid energy storage system, the battery pack converter adopts constant power control. Supercapacitors have high power density and fast charge and discharge response, and can quickly respond to bus voltage fluctuations. Therefore, the preceding DC converter, i.e., the bidirectional DC / DC converter, adopts bus voltage constant control. The design process is as follows: Derivative equation (3) is converted into a second-order ADRC form: (31) In formula (31): b sc is the control quantity gain, u 2 is the converter switch control signal, f sc is the total disturbance inside and outside the system, as shown in the following formula: (32) Select state quantity , ,make , and expand it into a first-order state, then design the following observer: (33) In formula (33): e 2 is the observation bias; z 1. z 2. z 3 for x 1. x 2. f sc estimated value; φ sc1 、 φ sc2 、 φ sc3 is the gain coefficient; Select the following linear sliding surfaces: (34) In formula (34): is the sliding surface coefficient, and satisfies ; Defining systematic error , and the improved exponential reaching law designed in Example 5 is selected as the switching control law, then the feedback control law is shown as follows: (35) In formula (35): u 2 is the switch tube T c1 、 T c2 Control signal.

[0031] In summary, the overall control structure of the system can be obtained as follows Figure 8 As shown, Figure 8 middle, u 1 is the switch tube T b1 、 T b2 control signal, u MPPT For the switch tube T p2 On-duty cycle.

[0032] Simulation analysis The Simulink platform was used to build Figure 1 The simulation model of the photovoltaic hybrid energy storage system shown in Figure 1 is shown. Traditional grid-connected energy storage converters typically use PI control, which is sensitive to system changes, has limited anti-disturbance capabilities, and relies on a precise mathematical model of the system. Therefore, to verify the feasibility of the improved sliding-mode active disturbance rejection control method of the present invention for a grid-connected photovoltaic hybrid energy storage converter, a comparative analysis was conducted between the present control method, PI control, and traditional sliding-mode control, assuming the same circuit model parameters. The system circuits and control parameters are shown in Tables 1 and 2.

[0033] Table 1 Circuit model parameters

[0034] Table 2 Controller parameters

[0035] 1) DC bus voltage dynamic response In the grid-connected state, in order to compare the transient performance of the system when the light intensity changes, the corresponding photovoltaic changes are set in the simulation. The corresponding photovoltaic output power when the light intensity changes P pv like Figure 9 shown.

[0036] The DC bus voltage response under different control conditions is shown in Figure 10. The temperature is set to 25°C and the initial light intensity (W / m 2 ) is 1000, drops to 800 at 2s, rises to 1200 at 4s, and returns to the initial illumination at 6s. The output power of the converter is 150kW.

[0037] As shown in Figure 10, when the photovoltaic power fluctuates, the three control strategies can all achieve effective tracking of the system status. However, the PI control strategy is accompanied by a large overshoot phenomenon during the startup phase and when the photovoltaic power jumps; the control method of the present invention effectively suppresses the overshoot problem and suppresses the ripple pulsation to about 0.8V, so that the system can recover to steady-state operation more quickly. During the three transient processes, regardless of whether the photovoltaic power drops or rises, under the premise of ensuring the convergence speed, the control method of the present invention has the best performance in reducing overshoot and smoothing ripples, followed by the traditional SMC strategy, and the PI control effect is the worst.

[0038] 2) Output power dynamic response In order to verify the impact of load switching on the dynamic performance of the system, the system is simulated by setting the corresponding active power instruction mutation and maintaining the light intensity at 1000W / m 2 The PV output power is 120 kW, and the converter's active power command is initially set at 150 kW. This command drops to 135 kW after 2 seconds, increases to 165 kW after 4 seconds, and returns to the initial command after 6 seconds. Because the upstream and downstream converters of the PV hybrid energy storage system are coupled via the DC bus, changes in the converter's active power command cause fluctuations in the DC bus voltage. Figure 11 shows the system responses under different control strategies.

[0039] As shown in Figure 11(a), when the system active power command changes, the three control strategies shown in the figure can all respond quickly to the output command and establish a new stable operating state. However, there is a large gap in control accuracy. PI control is accompanied by obvious overshoot and large ripple, and the waveform jitter phenomenon is serious; traditional SMC effectively suppresses power overshoot, but the effect of smoothing jitter is still not ideal; the control method of the present invention suppresses power ripple to about 0.2kW while ensuring response speed. As shown in Figure 10(b), the control method of the present invention can suppress bus voltage fluctuations to about 0.8V, which is significantly better than PI control and traditional SMC strategies. Under the condition of consistent control accuracy requirements, the control method of the present invention can achieve control requirements faster and more accurately.

[0040] Therefore, during the process of active power instruction mutation, the control method of the present invention has better anti-interference ability, can effectively limit power overshoot, suppress power and bus voltage pulsation, ensure that the system runs faster and more stably in the set state, and effectively improve the converter control performance.

[0041] To address the large fluctuations in grid-side power and bus voltage in grid-connected energy storage systems, this paper designs an improved sliding-mode active disturbance rejection control strategy based on a quasi-continuous algorithm, based on VSG technology. The voltage loop uses PI control to provide a reference signal for the current loop, which then uses the designed improved sliding-mode active disturbance rejection control strategy to enhance the dynamic performance of the photovoltaic hybrid energy storage converter. The following conclusions were drawn through theoretical analysis and simulation experiments: 1) The HO-STSMO has been improved based on the feedforward concept, which improves the observation accuracy and speed. It can cope with complex working conditions such as different lighting conditions and load changes, and can more accurately track and compensate for system power and voltage disturbances with faster response speed. 2) Compared with PI control and traditional SMC, the IQC-ITSMC control strategy proposed in the control method of the present invention adopts a dual sliding mode switching controller, which can provide continuous and smooth control signals during PV-HPCS operation, effectively suppressing power and bus voltage fluctuations and overshoot problems, and can enhance the reliability of the photovoltaic hybrid energy storage system and reduce the risk of system failures caused by voltage fluctuations. At the same time, the stable voltage environment can reduce the stress of power system equipment, extend the service life of equipment, reduce maintenance costs, improve the energy efficiency of the photovoltaic hybrid energy storage system, and enhance the stability of system operation. 3) Subsequent research will further study the control strategy of the grid-connected hybrid energy storage system operating under an unbalanced power grid based on the existing work, so as to solve the problem of oscillation during converter operation and the degradation of output voltage and current quality.

Claims

1. An improved sliding mode active disturbance rejection control method for a grid-connected photovoltaic hybrid energy storage converter is characterized in that: Please follow the steps below to implement it: Step 1: Establish the mathematical model of the converter and the state equation of the front-stage DC converter based on the photovoltaic hybrid energy storage system; Step 2: Network-based VSG control design By embedding the control algorithm into the mathematical model of the synchronous machine, the stationary power electronic device can simulate the behavior of the rotating machine. Based on this, the active and reactive power can be controlled by adjusting the output voltage and current of the converter. Step 2.1: P - f Speed ​​controller design; Step 2.2: Q - E Excitation controller design; Step 3: Converter control design; Step 3.1: Design of high-order super-helical sliding mode observer; Step 3.2: Converter Controller Design Step 4: Pre-stage DC converter control design.

2. The improved sliding mode active disturbance rejection control method for a grid-connected photovoltaic hybrid energy storage converter according to claim 1 is characterized in that: The step 1 is specifically as follows: The photovoltaic hybrid energy storage system includes a photovoltaic array, an energy storage unit, a bidirectional DC / DC converter, an inverter, an AC load and a distribution network. The energy storage unit includes a battery and a supercapacitor. The battery and supercapacitor are connected to the bidirectional DC / DC converter. The bidirectional DC / DC converter is connected to the subsequent converter, the distribution network and the AC load in sequence through the DC bus. The photovoltaic array is connected to the DC bus through the Boost boost circuit. A filtering link is provided between the subsequent converter and the distribution network. The Boost boost circuit includes a set of switch tubes. T p1 、 T p2 The bidirectional DC / DC converter connected to the battery includes a switch tube T b1 、 T b2 and inductance L b The bidirectional DC / DC converter connected to the supercapacitor includes a switch tube T c1 、 T c2 and inductance L c , T b1 、 T b2 and T c1 、 T c2 There are two pairs of complementary conducting switch tubes. The converter includes 6 switch tubes in the upper and lower bridge arms. s 1. s 2. s 3 、s 4. s 5. s 6; According to Kirchhoff's law, the mathematical model of the converter in the abc three-phase stationary coordinate system is: (1) In formula (1): u Ca 、u Cb 、u Cc For AC capacitance measurement C Voltage across both ends; s ka 、s kb 、s kc is the converter three-phase bridge arm switch control signal, u a 、 u b 、 u c is the three-phase voltage on the AC side of the converter; i a 、i b 、i c is the three-phase current after converter filtering, i sa 、 i sb 、 i sc is the three-phase current on the AC side of the converter, L 、 C For filter inductors and capacitors, R is the equivalent resistance of the circuit, e a 、 e b 、 e c is the AC grid voltage, i s is the DC side output current of the converter, i C is the DC bus current; Perform Park transformation on equation (1), and the mathematical model of the converter in the dq rotating coordinate system is: (2) In formula (2): ω is the angular frequency of the grid voltage; e d 、i d 、u Cd 、s d is the d-axis grid voltage, current, capacitor voltage and switching function, e q 、i q 、u Cq 、s q are q-axis grid voltage, current, capacitor voltage and switching function respectively; The state equation of the front-stage DC / DC converter is as follows: (3) In formula (3): D 1. D 2 are switching tubes T b1 、 T c1 On duty cycle, D 3 is the switch tube T p2 Shutdown duty cycle, u bat 、 u suc 、 u pv They are the output voltages of the battery pack, supercapacitor, and photovoltaic array respectively. i bat 、 i suc 、 i pv They are the output currents of the battery pack, supercapacitor and photovoltaic array respectively. u dc is the DC bus voltage.

3. The improved sliding mode active disturbance rejection control method for a grid-connected photovoltaic hybrid energy storage converter according to claim 2 is characterized in that: The step 2.1 is specifically as follows: According to Newton's second law, the mechanical equation of the virtual synchronous generator, that is, the rotor motion equation, is expressed as follows: (4) In formula (4): J is the moment of inertia; D is the damping coefficient; P m 、 P e is mechanical power and electromagnetic power; 、 are the reference angular velocity and the grid synchronization angular velocity; is the power angle; In order to simulate the frequency regulation characteristics of synchronous generators, a speed regulator is applied in VSG control, namely P - f The droop characteristics are as follows: (5) In formula (5): P ref is the reference active power; k f for P - f droop coefficient; Substitute equation (5) into equation (4) and perform Laplace transform: (6) According to formula (6), the phase reference information of the VSG terminal voltage is obtained ω* .

4. The improved sliding mode active disturbance rejection control method for a grid-connected photovoltaic hybrid energy storage converter according to claim 3 is characterized in that: The step 2.2 is specifically as follows: The synchronous generator adjusts the output reactive power and terminal voltage by adjusting the excitation. Similarly, the virtual potential of the virtual synchronous machine can be controlled E m The amplitude and phase of the reactive power are used to adjust the output reactive power to ensure the stability of the terminal voltage. Therefore, a voltage deviation is introduced into the VSG reactive power loop to adjust the system reactive power. The VSG reactive power and voltage droop characteristics are shown in the following formula: (7) In formula (7): Q ref is the reactive reference; U n is the effective value of the terminal voltage; U s is the actual output voltage of VSG; k q for QE droop coefficient; From formula (7), we know that by adjusting the VSG output voltage amplitude and phase, the system reactive power command is tracked to provide reactive power support for the photovoltaic hybrid energy storage system. E m The output will Q * and electromagnetic reactive power Q e Compare and integrate, and finally get the virtual potential E m The amplitude of .

5. The improved sliding mode active disturbance rejection control method for a grid-connected photovoltaic hybrid energy storage converter according to claim 4 is characterized in that: The step 3.1 is specifically as follows: Suppose the following second-order controlled object: (8) In formula (8): x is the system status, u ( t ) is the control input, b is the control quantity gain, f ( x , u ) are all uncertainties and unknown disturbances in the system; make , and expand it to a first-order state, then the above second-order system is expanded to the following form: (9) In formula (9): x 1 is the system status, x 2 is the system state differential, x 3 is the total disturbance of the system; For the system (8), the following high-order super-spiral sliding mode observer HO-STSMO is constructed: (10) In formula (10): e 1 is the observation error; z 1. z 2. z 3 for x 1. x 2. f estimated value; 、 、 is the gain coefficient; because In the presence of discontinuity, the discontinuous switching term is replaced by a hyperbolic function. Based on the feedforward theory, the super-helical sliding mode observer is improved as follows: First, transform Equation (2) to obtain the state variables d and q axis currents i sd 、 i sq The first-order differential form is as follows: (11) The d-axis and q-axis current coupling terms and the unmodeled part are regarded as lumped disturbances, respectively. f d 、 f q Expressed as follows, the derivative of Equation (11) is converted into the second-order ADRC paradigm as follows: (12) In formula (12): b o for b Estimated value, f d 、 f q As shown below: (13) Take the feedforward error signal for the above system , i ref is the current reference value, find its second-order derivative and substitute equation (12) into it: (14) Select state variables , , , then the system shown in formula (12) is transformed into: (15) For the feedforward error system shown in Equation (15), the lumped disturbances of the d and q axes are f d 、 f q Expand to new state variables z d3 、 z q3 , then design the d-axis and q-axis observers respectively; The designs of the d-axis and q-axis high-order super-helical sliding mode observers are as follows: (16) (17) In formula (16) to formula (17): e d1 、 e q1 is the state observation error; z d1 、 z d2 、 z d3 and z q1 、 z q2 、 z q3 They are x d1 、 x d2 、 f d and x q1 、 x q2 、 f q estimated value of; φ d1 、 φ d2 、 φ d3 and φ q1 、 φ q2 、 φ q3 are the d-axis and q-axis observer gains respectively.

6. The improved sliding mode active disturbance rejection control method for a grid-connected photovoltaic hybrid energy storage converter according to claim 5, characterized in that: The hyperbolic function F( e i ) is shown in the following formula: (18)。 7. The improved sliding mode active disturbance rejection control method for a grid-connected photovoltaic hybrid energy storage converter according to claim 6, characterized in that: The step 3.2 is specifically as follows: Design and improve the second-order quasi-continuous integral terminal sliding mode controller IQC-ITSMC. The specific process is as follows: definition 、 is the system state deviation of the d and q axes, as shown below: (19) According to formula (19), the following integral terminal sliding surface is designed: (20) In formula (20): , ; α , β is the sliding surface adaptive control parameter, and its expression is as follows: (21) In formula (21): 、 is the adaptive gain, both greater than 0; Differentiate equation (20) and substitute equation (15) into it to obtain: (22) (23) Since the system converges in finite time, according to the equivalent control theory, let , we get the system equivalent control law of d and q axes: (24)； As shown in formula (23), the sliding surface The control quantity appears for the first time in the second-order differential s , so the relative order of the system is 2. In order to generate a continuous control signal, a second-order quasi-continuous algorithm is introduced as the sliding mode switching control law, which is designed as follows: (25) In formula (25): l d 、 l q are the proportional coefficients of the d-axis and q-axis switching controllers, is a saturation function, as shown below: (26) In formula (26): is the boundary layer thickness; The improved exponential reaching law is designed as the second-stage switching controller of the sliding mode motion as shown below: (27) In formula (27): 、 is the reaching law gain coefficient, all greater than 0; In summary, the system switches the controller s sw , the design is as follows: (28) In formula (28): Switch controller for d axis, 、 Switching control law for the d-axis Switch controller for the q axis, is the q-axis switching control law, γ is the switching term, which ensures the switching control law s sw1 and s sw2 The working state is switched under the following conditions: (29) In formula (29): is a positive constant; Combining equations (24) and (28), we can obtain the second-order quasi-continuous sliding mode control law of the photovoltaic hybrid energy storage converter system as follows: (30)。 8. The improved sliding mode active disturbance rejection control method for a grid-connected photovoltaic hybrid energy storage converter according to claim 7, characterized in that: The step 4 is specifically as follows: The bus voltage constant control is adopted for the front-stage DC converter, i.e. the bidirectional DC / DC converter. The design process is as follows: Derivative equation (3) is converted into a second-order ADRC form: (31) In formula (31): b sc is the control quantity gain, u 2 is the converter switch control signal, f sc is the total disturbance inside and outside the system, as shown in the following formula: (32) Select state quantity , ,make , and expand it into a first-order state, then design the following observer: (33) In formula (33): e 2 is the observation bias; z 1. z 2. z 3 for x 1. x 2. f sc estimated value; φ sc1 、 φ sc2 、 φ sc3 is the gain coefficient; Select the following linear sliding surfaces: (34) In formula (34): is the sliding surface coefficient, and satisfies ; Defining systematic error , and the improved exponential reaching law is selected as the switching control law, then the feedback control law is as follows: (35) In formula (35): u 2 is the switch tube T c1 、 T c2 Control signal.

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