A Sliding Mode Active Disturbance Rejection Control Method for Photovoltaic-Storage System Considering Source-Load Power Fluctuations

Abstract

The present invention belongs to the technical field of photovoltaic energy storage system control, and particularly relates to a sliding mode auto-disturbance rejection control method for a photovoltaic energy storage system considering source-load power fluctuations. The method includes the following steps: Step S1: Considering the power fluctuations of the source and load in the photovoltaic energy storage system, analyze the charging and discharging behavior of the storage battery, construct a mathematical model of the storage battery-photovoltaic system, and obtain the corresponding state equation; Step S2: Based on the sliding mode control and auto-disturbance rejection control principles, design the controller structure according to the mathematical model constructed in Step S1, and design the current loop; Step S3: Design each part of the voltage loop and introduce it into the controller structure designed in Step S2. By adopting the above technical means, when the source / load power fluctuates, the stable control of the bus voltage of the photovoltaic energy storage system and the reasonable distribution of power are realized, so that the photovoltaic energy storage system operates safely and stably.

Description

Technical Field

[0001] The present invention belongs to the technical field of photovoltaic energy storage system control, and particularly relates to a sliding mode active disturbance rejection control method for a photovoltaic energy storage system considering source-load power fluctuations. Background Art

[0002] The advantage of photovoltaic power generation is that it can directly convert solar energy into electrical energy and has no pollution during operation, so it is regarded as an important direction for future energy development. However, as the "source" side of the photovoltaic power generation system, the output power of the photovoltaic module is affected by the intensity of light and the temperature, and thus has uncertainty. As the "load" side of the photovoltaic power supply system, due to the variety of load types and user electricity consumption habits, the magnitude of the power consumed also has great uncertainty. The introduction of the energy storage system provides important technical support for the application of photovoltaic power generation. Through energy storage devices, the system can store electrical energy when power generation is excessive and release electrical energy when power generation is insufficient, thus balancing the mismatch between power generation and power consumption. Therefore, it is very important to control the photovoltaic energy storage system.

[0003] Currently, the control methods for photovoltaic energy storage systems mainly include PI control, sliding mode control, linear active disturbance rejection control, etc. If sliding mode control is used alone, although it is suitable for systems with strong uncertainty and disturbances, the chattering problem needs to be solved; the response speed of traditional PI control depends on parameter tuning. Although the response speed can be adjusted within a certain range, it is difficult to quickly adjust when the system state and external disturbances change greatly. At the same time, when a sudden external disturbance occurs, the controller needs a certain time to adjust the output to return to the set point; linear active disturbance rejection control has good anti-disturbance performance and robustness and is suitable for dealing with complex non-linear or time-varying systems. However, its traditional differential link usually assumes that the input signal is smooth, so there are problems of poor accuracy and sensitivity to signals; at the same time, the anti-disturbance ability mainly depends on the observer (ESO), and if its coefficient is too large, it will increase the influence of high-frequency noise on the system, thus limiting the upper limit of the anti-interference ability of the photovoltaic energy storage system. Therefore, in view of the defects in the current existing technologies, it is necessary to conduct research and analysis to provide a composite control scheme to make the photovoltaic energy storage system have high robustness when the source-load power fluctuates. Summary of the Invention

[0004] To solve the above technical problems, the present invention provides a sliding mode active disturbance rejection control method for a photovoltaic energy storage system considering source-load power fluctuations.

[0005] To achieve the above object, the present invention adopts the following technical solutions:

[0006] A sliding mode active disturbance rejection control method for a photovoltaic energy storage system considering source-load power fluctuations, comprising the following steps:

[0007] Step S1: Considering the power volatility of the source and load in the photovoltaic and energy storage system, analyze the charging and discharging behavior of the battery, construct a mathematical model of the battery - photovoltaic system, and obtain the corresponding state equation;

[0008] Step S2: Based on the sliding - mode control and auto - disturbance rejection control principles, design the controller structure according to the mathematical model constructed in Step S1, and design the current loop;

[0009] Step S3: Design each part of the voltage loop and introduce it into the controller structure designed in Step S2 to achieve stable control of the bus voltage of the photovoltaic and energy storage system and reasonable power distribution when the source - load power fluctuates.

[0010] Further, in Step S1, the consideration of the power volatility of the source and load in the photovoltaic and energy storage system, the analysis of the charging and discharging behavior of the battery, the construction of a mathematical model of the battery - photovoltaic system, and the obtaining of the corresponding state equation are specifically as follows: Analyze the charging and discharging behavior of the lithium - battery and analyze the topology of the half - bridge bidirectional Buck / Boost converter in the photovoltaic system, construct a mathematical model of the battery - photovoltaic system, and obtain the corresponding state equation.

[0011] Further, the analysis of the charging and discharging behavior of the lithium - battery, the analysis of the topology of the half - bridge bidirectional Buck / Boost converter in the photovoltaic system, the construction of a mathematical model of the battery - photovoltaic system, and the obtaining of the corresponding state equation are specifically as follows:

[0012] Step S11: Analyze the charging and discharging behavior of the battery, establish its equivalent circuit model, and obtain the output characteristic equation as:

[0013]

[0014] where U oc is the open - circuit voltage of the battery, U p and U B are the terminal voltages of the RC circuit and the battery respectively, I is the current of the battery, and R1, R2, and C are the internal resistance, polarization resistance, and polarization capacitance of the battery respectively;

[0015] Use the ampere - hour integration method to calculate the state of charge of the battery, and obtain the following formula:

[0016]

[0017] where SOC(t s ) represents the state of charge of the battery, E Bmax represents the total energy of the battery, t0 and t s are the start time and end time of the integration process respectively, and I bRepresents the output current of the storage battery. When it is positive, the battery is in the discharging state; conversely, the battery is in the charging state.

[0018] Step S12: Analyze the charging and discharging states of the half-bridge bidirectional Buck / Boost converter interface circuit of the photovoltaic system, and obtain the equivalent state equation as:

[0019]

[0020] In the formula, L is the inductor, C B and C dc are the filter capacitors, U B and U dc are the energy storage side voltage and the DC bus voltage respectively, I B and I L are the energy storage side current and the inductor current respectively, R eq is the equivalent load on the bus side, and can be specifically expressed as:

[0021]

[0022] In the formula, U dc is the DC bus voltage, R is the load, and P CPL is the sum of the photovoltaic power generation output power and the power consumed on the DC bus.

[0023] Furthermore, in step S2, based on the sliding mode control and auto-disturbance rejection control principles, design the controller structure according to the mathematical model constructed in step S1, and design the current loop. The specific design of the current loop is as follows:

[0024] The current loop adopts sliding mode control, and the mathematical model of sliding mode control is:

[0025]

[0026] In the formula, U dc is the DC bus voltage, I L is the inductor current, f(U dc , I L ) is the non-linear relationship between the DC bus voltage and the inductor current, and ω1 is the influence of the photovoltaic energy storage system on the current;

[0027] Set the current loop sliding mode surface s' as:

[0028] s' = I L -I Lref (6)

[0029] In the formula, s' represents the current loop sliding mode surface, I L is the inductor current, and I Lref is the reference value of the inductor current;

[0030] Design \(u_1\) to make the system state tend to and remain on the sliding surface, specifically expressed as:

[0031]

[0032] where \(u_1\) is the corresponding sliding mode control law, \(b\) i is the compensation coefficient, \(k\) i is the main control parameter, and \(\text{sgn}(e)\) is the sign function.

[0033] Furthermore, in step S3, the design of each part of the voltage loop specifically includes the following steps:

[0034] Step S31: Design a sliding mode differential estimator;

[0035] Step S32: Design a sliding mode extended state observer;

[0036] Step S33: Design an error feedback controller.

[0037] Furthermore, in step S31, the design of the sliding mode differential estimator is specifically as follows:

[0038] The sliding mode differential estimator model is described by the following differential equation:

[0039]

[0040] where \(x_1\) is the output signal of the sliding mode differential estimator, \(x_2\) is the derivative estimate of the output signal, \(k\) is the switching gain used to adjust the intensity of the sliding mode differential, \(\text{sgn}(e)\) is the sign function, and \(U\) dcref is the DC bus voltage reference value;

[0041] Define the sliding surface \(s''\) of the sliding mode differential estimator:

[0042] \(s'' = x_1 - U\) dcref (9)

[0043] where \(s''\) represents the sliding surface of the sliding mode differential estimator. When \(s'' = 0\), the system will move on the sliding surface, making \(x_1\) track \(U\) dcref ;

[0044] Discretizing the above continuous system, we can obtain:

[0045]

[0046] where \(k_0\) is the switching gain and \(T\) s is the sampling period.

[0047] Furthermore, in step S32, the design of the sliding mode extended state observer specifically includes the following steps:

[0048] Step S321. The non - linear function expression of the DC bus voltage input and output is:

[0049]

[0050] In the formula, L is the inductor, C dc is the filter capacitor, U dc is the DC bus voltage, I L is the inductor current, R eq is the equivalent load on the bus side, and ω represents the disturbance received by the system;

[0051] The disturbance function f1(U dc , ω, t) and the control variable gain b are defined respectively, and their expressions are:

[0052]

[0053] In formula (12), f1(U dc , ω, t) is the disturbance function, and b is the control variable gain;

[0054] After arranging formulas (11) and (12), an expression linearly combined by the system input U dc and the system output I L is obtained:

[0055]

[0056] The control variable gain b is an inherent parameter of the system, and it is difficult to obtain its actual value. Therefore, let b0 be the estimated value of b, and we get:

[0057]

[0058] In the formula, b0 is the estimated value of b;

[0059] Step S322. Take the state variables x1 = U dc , x2 = f, let the vector x = [x1, x2], and the state - space equation form of the system is obtained as:

[0060]

[0061] Among them C = [1 0], D = [0],

[0062] Let the state vector z = [z1, z2], where the state variable z1 is used to track the DC bus voltage U dc , and the state variable z2 is used to track the total disturbance; The linear extended state observer is expressed in the following state - space equation form:

[0063]

[0064] where \(F = [\beta_1, \beta_2]\) T , and \(\beta_1\) and \(\beta_2\) are the gains of error feedback;

[0065] Using the pole placement method and performing Laplace transform, we get:

[0066]

[0067] In the formula, \(\omega_0\) is the bandwidth parameter;

[0068] Step S323, the state space equation of the sliding mode extended state observer is:

[0069]

[0070] In the formula, \(k_1\), \(k_2\) are the sliding mode gain parameters, \(s''\) represents the sliding mode surface of the sliding mode differential estimator, \(L_0\) is the controller gain, and adjust \(k_1\), \(k_2\) to make the characteristics of the sliding mode extended state observer match Equation (17);

[0071] According to the error state, design \(u_2\) to make the system state tend to the sliding mode surface and stay on it, specifically expressed as:

[0072]

[0073] In the formula: \(u_2\) is the corresponding sliding mode control law, represents the compensation for the total disturbance, \(k\) u is the error compensation coefficient, and sgn(e) is the sign function.

[0074] Furthermore, in step S33, the design of the error feedback controller is specifically:

[0075] The error feedback controller consists of two parts: a disturbance compensation unit and a proportional control unit. Let \(u_0\) be the output of the error feedback controller, then the implementation form of the disturbance compensation unit is:

[0076]

[0077] In the formula, \(I\) Lref is the reference value of the inductor current; \(u_0\) is the output of the error feedback controller, \(b_0\) is the estimated value of the control quantity gain \(b\), and \(u_0 / b_0\) represents the ideal control signal before disturbance compensation; \(z_2\) is the state variable used to track the total disturbance, and the role of \(-z_2 / b_0\) is to reduce the influence of the total disturbance estimated by the sliding mode extended state observer;

[0078] After substituting Equation (20) into (14) and taking the limit, we get:

[0079]

[0080] The system is simplified to a single-integral system, so a proportional controller is designed as follows:

[0081] u0 = ω c (x1 - z1) (22)

[0082] In Equations (21) and (22), z1 is the state variable used to track the DC bus voltage U dc , ω, t) is the disturbance function, and ω dc is the controller gain. c

[0083] The present invention also provides a computer storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the above-mentioned sliding mode active disturbance rejection control method for a photovoltaic energy storage system considering source-load power fluctuations are realized.

[0084] Compared with the prior art, the present invention has the following beneficial technical effects:

[0085] (1) Different from the traditional method of directly adopting a single battery or photovoltaic system model, this patent truly considers the power volatility on the "source" side and the load side, utilizes the power interaction between the energy storage module and the DC bus, takes the bidirectional interface converter as the interface, studies the charging and discharging behavior of the battery from the mechanism, and then establishes a combined battery-photovoltaic system model to improve the modeling accuracy of the photovoltaic energy storage system.

[0086] (2) In an actual photovoltaic energy storage control system, the traditional differential link is very sensitive to noise and easily amplifies the high-frequency noise in the signal, resulting in a decline in the performance of the control system. The present invention innovatively proposes a differential solution method based on sliding mode control, which not only solves the sensitivity problem of the differential link but also enhances the robustness and anti-noise ability of the system.

[0087] (3) On the basis of active disturbance rejection control, the present invention introduces a sliding mode control method, specifically a sliding mode differential estimator and a sliding mode extended state observer, which improves the parameter tuning of the control system. Therefore, the sliding mode active disturbance rejection control method of the present invention can improve the energy utilization rate, response speed, and robustness of the photovoltaic energy storage system compared with the traditional PI control method, enabling it to cope with source-load power fluctuations. Brief Description of the Drawings

[0088] Figure 1 is a typical structure diagram of the photovoltaic energy storage system of the present invention;

[0089] Figure 2 is a model diagram of the lithium-ion battery of the present invention;

[0090] Figure 3 ​This is the topology diagram of the energy storage side interface of the half-bridge bidirectional charge / discharge converter adopted by the present invention;

[0091] Figure 4 This is the circuit structure diagram of different switch states under the charge / discharge state of the present invention,

[0092] Figure 4 (a) is the Buck mode, VT1 is turned on, and VT2 is turned off,

[0093] Figure 4 (b) is the Buck mode, VT1 is turned off, and VT2 is turned off,

[0094] Figure 4 (c) is the Boost mode, VT1 is turned off, and VT2 is turned on,

[0095] Figure 4 (d) is the Boost mode, VT1 is turned off, and VT2 is turned off;

[0096] Figure 5 This is the design block diagram of the controller of the photovoltaic and energy storage system of the present invention;

[0097] Figure 6 is the simulation result diagram of the output power P PV of the photovoltaic array in the embodiment,

[0098] Figure 6 (a) is the curve of the change of the external environment, Figure 6 (b) is the change of the output power P PV of the photovoltaic panel;

[0099] Figure 7 is the change diagram of the power P B of the energy storage battery and the SOC under different control strategies in the embodiment,

[0100] Figure 7 (a) is the change of the power P B of the energy storage battery, Figure 7 (b) is the change of the SoC of the energy storage battery;

[0101] Figure 8 is the simulation result diagram of the DC bus voltage U dc under different control strategies in the embodiment;

[0102] Figure 9 is the curve of the change of the constant power load power in the embodiment;

[0103] Figure 10 is the simulation result diagram of the power P B of the energy storage battery and the SOC under different load powers in the embodiment,

[0104] Figure 10(a) is the power P of the storage battery B variation, Figure 10 (b) is the variation of the SoC of the storage battery;

[0105] Figure 11 is the variation diagram of the DC bus voltage U under different load powers in the embodiment dc of. Specific implementation manner

[0106] The following further explains the present invention in detail with reference to the drawings, so that those skilled in the art can understand the present invention more deeply and be able to implement it.

[0107] Different from the traditional method of directly adopting a single storage battery or photovoltaic system model, the present invention truly considers the power volatility of the "source" side and the "load" side, utilizes the power interaction between the energy storage module and the DC bus, takes the bidirectional interface converter as the interface, studies the charging and discharging behavior of the storage battery from the mechanism, and then establishes a combined model of the storage battery - photovoltaic system. And based on the active disturbance rejection control principle, designs a corresponding active disturbance rejection controller according to the established mathematical model; introduces a sliding mode differential estimator and a sliding mode extended state observer into the active disturbance rejection controller, realizes the stable control of the bus voltage of the photovoltaic - energy storage system and the reasonable distribution of power when the source - load power fluctuates, so that the photovoltaic - energy storage system operates safely and stably.

[0108] The present invention provides a sliding mode active disturbance rejection control method for a photovoltaic - energy storage system considering source - load power fluctuations, see Figures 1 to 5 , including the following steps:

[0109] Step S1, considering the power volatility of the source - load in the photovoltaic - energy storage system, analyzing the charging and discharging behavior of the storage battery, constructing a mathematical model of the storage battery - photovoltaic system, and obtaining the corresponding state equation.

[0110] See Figure 1 , the photovoltaic - energy storage system mainly includes a photovoltaic module, an energy storage module, and a load module; the main body of the energy storage module is a storage battery pack, and the two - way transmission of electric energy is carried out with the DC bus through a DC - DC converter; at the same time, the "source" side (photovoltaic module) and the "load" side (user load) are also connected to the DC bus through a converter.

[0111] In the photovoltaic - energy storage system, lithium batteries are mostly used for the storage battery, and its working principle is based on the movement of lithium ions through the electrolyte between the positive and negative electrodes of the battery to achieve energy storage and release; the power interaction control between the energy storage module and the DC bus often uses a half - bridge bidirectional Buck / Boost converter. Therefore, in the present invention, the charging and discharging behavior of the lithium battery is analyzed, and the topology of the half - bridge bidirectional Buck / Boost converter of the photovoltaic system is analyzed, a mathematical model of the storage battery - photovoltaic system is constructed, and the corresponding state equation is obtained.

[0112] The specific steps of step S1 are as follows:

[0113] Step S11. Refer to Figure 2 , the modeling of the lithium battery includes an electrochemical model and an equivalent circuit model. Analyze the charging and discharging behaviors of the battery, establish its equivalent circuit model, and obtain the output characteristic equation as:

[0114]

[0115] In the formula, U oc is the open-circuit voltage of the battery, U p and U B are the terminal voltages of the RC circuit and the battery respectively, I is the current of the battery, and R1, R2, and C are the internal resistance, polarization resistance, and polarization capacitance of the battery respectively.

[0116] In order to accurately estimate the state of charge (SOC) of the storage battery, the ampere-hour integration method is used for calculation:

[0117]

[0118] In the formula, E Bmax represents the total energy of the battery, t0 and t s are the start time and end time of the integration process respectively; I b represents the output current of the storage battery. When it is positive, the battery is in the discharge state, and vice versa, the battery is in the charging state.

[0119] Step S12. Analyze the charging and discharging states of the half-bridge bidirectional Buck / Boost converter interface circuit of the photovoltaic system to obtain the equivalent state equation. Refer to Figure 3 .

[0120] Analyze the charging and discharging states of the energy storage side interface circuit. The specific analysis process can be referred to Figure 4 , and the equivalent state equation can be obtained as:

[0121]

[0122] In the formula, L is the inductor, C B and C dc are the filter capacitors, U B and U dc are the energy storage side voltage and the DC bus voltage respectively, I B and I L are the energy storage side current and the inductor current respectively. R eq is the equivalent load on the bus side, which can be specifically expressed as:

[0123]

[0124] Wherein, U dc is the DC bus voltage, R is the load, and P CPL is P S (photovoltaic power generation output power) and P L (power consumed on the DC bus). When R eq is greater than zero, it indicates that the bus side is consuming power. At this time, the photovoltaic energy storage system is mainly affected by the "source" side; conversely, it is affected by the "load" side.

[0125] Step S2: Based on the sliding mode control and active disturbance rejection control principles, design the controller structure according to the mathematical model constructed in Step S1, and design the current loop.

[0126] See Figure 5 , which is the design block diagram of the photovoltaic energy storage system controller. The controller structure includes two parts: a voltage loop and a current loop. Among them, the current loop adopts sliding mode control, and the voltage loop adopts an active disturbance rejection control structure. The specific design steps of the voltage loop are described in Step S3.

[0127] The specific design of the current loop is as follows:

[0128] Different from the traditional PI control, the current loop adopts sliding mode control to achieve fast tracking and response of the inductor current. The mathematical model of sliding mode control is:

[0129]

[0130] Wherein, U dc is the DC bus voltage, I L is the inductor current, f(U dc , I L ) is the non-linear relationship between the DC bus voltage and the inductor current, and ω1 is the influence of the photovoltaic energy storage system on the current.

[0131] Set the current loop sliding mode surface s' as:

[0132] s' = I L - I Lref (6)

[0133] Wherein, s' represents the current loop sliding mode surface, I L is the inductor current, and I Lref is the inductor current reference value.

[0134] Design u1 to make the system state tend to the sliding mode surface and stay on it, which is specifically expressed as:

[0135]

[0136] Wherein u1 is the corresponding sliding mode control law, b iis the compensation coefficient used to offset the interference of the system itself; k i is the main control parameter that determines the effect of sliding mode control; Sign function.

[0137] Step S3: Design each part of the voltage loop and introduce it into the controller structure designed in Step S2 to achieve stable control of the bus voltage of the energy storage system and reasonable power distribution when the source-load power fluctuates.

[0138] Design the voltage loop, adopt the active disturbance rejection control structure, and the controlled object is the DC bus voltage U dc , which is smoothed by a sliding mode differential estimator, mainly used to extract the true dynamics of the system from noise. After smoothing, a sliding mode extended state observer is used to estimate external disturbances and system uncertainties. The sliding mode extended state observer is a technology that combines the idea of sliding mode control and the extended state observer. It can not only estimate the system state but also predict the impact of disturbances on the system. Finally, the control quantity is compensated by an error feedback controller. The error feedback controller adjusts according to the error of the system (i.e., the deviation between the target and the actual state) and uses a compensation mechanism to correct the output of the system.

[0139] Design each part of the voltage loop, which specifically includes the following steps:

[0140] Step S31: Design a sliding mode differential estimator, specifically:

[0141] The sliding mode differential estimator model can be described by the following differential equation:

[0142]

[0143] where x1 is the output signal of the sliding mode differential estimator, x2 is the derivative estimate of the output signal, k is the switching gain used to adjust the intensity of the sliding mode differential, sgn(e) is the sign function, and U dcref is the DC bus voltage reference value.

[0144] Define the sliding mode surface s” of the sliding mode differential estimator:

[0145] s” = x1 - U dcref (9)

[0146] where s” represents the sliding mode surface of the sliding mode differential estimator. When s” = 0, the system will move on the sliding mode surface, making x1 track U dcref ;

[0147] The sliding mode differential estimator is usually implemented in a discretized form. Discretizing the above continuous system, we can get:

[0148]

[0149] where \(k_0\) is the switching gain and \(T\) s is the sampling period.

[0150] Step S32: Design a sliding mode extended state observer. The design of the sliding mode extended state observer is improved based on the general linear extended state observer. The specific improvements include the following steps:

[0151] Step S321: Since the outer-loop controlled variable, i.e., the DC bus voltage \(U\) dc changes more slowly and with a smaller amplitude than the inner-loop controlled variable, i.e., the inductor current \(I\) L . Therefore, the nonlinear function expression of the input and output of the DC bus voltage can be derived from the interface converter model expressed by formula (3) as:

[0152]

[0153] where \(L\) is the inductor, \(C\) dc is the filter capacitor, \(U\) dc is the DC bus voltage, \(I\) L is the inductor current, \(R\) eq is the equivalent load on the bus side, and \(\omega\) represents the disturbance suffered by the system.

[0154] Define the disturbance function \(f_1(U\) dc , \(\omega, t)\) and the control quantity gain \(b\) respectively. Their expressions are

[0155]

[0156] In formula (12), \(f_1(U\) dc , \(\omega, t)\) is the disturbance function and \(b\) is the control quantity gain.

[0157] After organizing formulas (11) and (12), an expression linearly combined by the system input \(U\) dc and the system output \(I\) L can be obtained:

[0158]

[0159] Since the control quantity gain \(b\) is an inherent parameter of the system and it is difficult to obtain its actual value, \(b_0\) can be set as the estimated value of \(b\), and we get:

[0160]

[0161] where \(b_0\) is the estimated value of \(b\).

[0162] Step S322: Let the state variable \(x_1 = U\) dc , \(x_2 = f\). Let the vector \(x = [x_1, x_2]\). Then, the state space equation form of the system can be obtained as:

[0163]

[0164] wherein C =

[10] , D = [0],

[0165] Let the state vector z = [z1, z2], wherein the state variable z1 is used to track the DC bus voltage U dc , and the state variable z2 is used to track the total disturbance. Therefore, the linear extended state observer can be expressed in the form of the following state space equation:

[0166]

[0167] where F = [β1, β2] T , and β1 and β2 are the gains of error feedback.

[0168] Using the pole placement method and performing Laplace transform, we can obtain:

[0169]

[0170] In the formula, ω0 is the bandwidth parameter.

[0171] Step S323, the state space equation of the sliding mode extended state observer is:

[0172]

[0173] In the formula, k1 and k2 are the sliding mode gain parameters, s” represents the sliding mode surface of the sliding mode differential estimator, and L0 is the controller gain. Adjust k1 and k2 to make the characteristics of the sliding mode extended state observer match Equation (17).

[0174] Similarly, according to the error state, design u2 to make the system state tend to the sliding mode surface and stay on it, specifically expressed as:

[0175]

[0176] In the formula: u2 is the corresponding sliding mode control law, represents the compensation for the total disturbance, k u is the error compensation coefficient, and sgn(e) is the sign function.

[0177] Step S33, design an error feedback controller. The error feedback controller consists of two parts: a disturbance compensation unit and a proportional control unit. Let u0 be the output of the error feedback controller, then the implementation form of the disturbance compensation unit is:

[0178]

[0179] Wherein, I Lref is the reference value of the inductor current; u0 is the output of the error feedback controller, b0 is the estimated value of the control quantity gain b, and u0 / b0 represents the ideal control signal before disturbance compensation; z2 is the state variable used to track the total disturbance, and the role of -z2 / b0 is to reduce the influence of the total disturbance estimated by the sliding mode extended state observer.

[0180] After substituting Equation (20) into (14) and taking the limit, we get:

[0181]

[0182] It can be seen from this that the system is simplified to a single-integral system, so a proportional controller can be designed as follows:

[0183] u0 = ω c (x1 - z1) (22)

[0184] In Equations (21) and (22), z1 is the state variable used to track the DC bus voltage U dc , f1(U dc , ω, t) is the disturbance function, and ω c is the controller gain.

[0185] The present invention also provides a computer storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the sliding mode auto-disturbance rejection control method for the photovoltaic energy storage system considering source-load power fluctuations are realized.

[0186] Embodiment:

[0187] The following further illustrates the specific implementation manners in combination with the embodiments. The present invention uses the corresponding simulation software to perform simulation verification according to the above implementation manners to evaluate the control effect of the control method of the present invention. Among them: the parameters of the photovoltaic module, that is, the "source" side, are set as shown in Table 1, and the circuit parameters of the energy storage side are shown in Table 2. Referring to Figure 1 , as the typical structure of the photovoltaic energy storage system, a simulation model of the photovoltaic energy storage system is built, and two cases of power fluctuations on the "source" side and the "load" side under the influence of light and temperature are considered respectively for simulation analysis.

[0188] Table 1 Photovoltaic panel parameters

[0189]

[0190] Table 2 Circuit parameters of the energy storage module

[0191]

[0192] According to the requirements of voltage and power, the photovoltaic panels are combined into a 2×4 photovoltaic array. The illumination received by the photovoltaic array is uniform, and the power consumed by the constant power load is fixed at 250W without change. The simulation duration is set to 1.5s, and the changes in the external environment are shown in Figure 6 (a), that is, the temperature is reduced from 25°C to 10°C at the simulation time t = 0.5s, and the light intensity is reduced from 1000W / m 2 to 300W / m 2 at the simulation time t = 1s.

[0193] It should be noted that the switching gain k0 of the sliding mode differential estimator in step S3 of the present invention is taken as 10, and the sampling period T s is taken as 5ms; the bandwidth parameter ω0 in the sliding mode extended state observer is taken as 20Hz; the sliding mode gain parameters k1 is taken as 40, k2 is taken as 400; the controller gain L0 is taken as 2; the error compensation coefficient k u is taken as 2. In the proportional controller, ω c is taken as 15.

[0194] The simulation results are shown in Figures 6 to 8 , where the change in the output power of the photovoltaic array is as shown in Figure 6 (b), the change in the output power and SOC of the battery is as shown in Figure 7 , and the change in the DC bus voltage U dc is as shown in Figure 8 .

[0195] See Figure 6 (b), which is the change in the output power of the photovoltaic array. It can be seen that the temperature change at t = 0.5s has little effect on the maximum power point of the photovoltaic array. The decrease in temperature slightly increases the maximum power of the photovoltaic. As the light intensity decreases significantly at t = 1s, the output power of the photovoltaic array also decreases significantly. In addition, under the control of the present invention, the maximum power of the photovoltaic array is slightly higher than that under the traditional control after t = 1s.

[0196] See Figure 7 , which is the change in the output power and SOC of the battery. The output power of the photovoltaic array and the output power of the battery under the control method of the present invention have smaller fluctuations compared with those under the PI double closed-loop control strategy. From t = 0 to t = 1s, the power provided by the photovoltaic array is greater than the power consumed by the load. Therefore, the power on the battery side is less than zero and it is in the charging state, and the SOC rises steadily; after t = 1s, the power provided by the photovoltaic array is less than the power consumed by the load, the power on the battery side is greater than zero, and it is in the discharging state, and the SOC drops steadily. In addition, it can be seen from Figure 7 (b) that the SOC loss of the battery under the control method of the present invention is less than that under the traditional control.

[0197] See Figure 8, which is the DC bus voltage U dc With the change of dc , under the control method of the present invention, when the external environment suddenly changes at t = 0.5 s and t = 1 s, the DC bus voltage of the system has a smaller overshoot and a shorter steady-state time. The detailed control performance data of the two are shown in Table 3.

[0198] Table 3 Performance comparison of two control methods considering environmental changes

[0199]

[0200] See Figure 9 , which is the power change curve of the constant power load. That is, when the power on the "load" side fluctuates, the power P of the constant power load Load is changed according to the curve shown in Figure 9 , that is, P is increased from 100 W to 300 W at t = 0.5 s, and a sinusoidal disturbance with an amplitude of 30 W is introduced at t = 1 s. Load

[0201] See Figure 10 , which is the simulation results of the power P B and SOC of the energy storage battery under different load powers. It can be seen that the control method of the present invention has a better control effect on the energy storage side when the load side changes compared with the traditional control. Under the control method of the present invention, the battery power has less jitter, making the charging and discharging process of the battery more stable. In addition, the value of the battery charging power after reaching the steady state is larger, and the battery SOC gradually increases, improving the energy utilization rate. In the same situation under traditional control, the battery SOC gradually decreases.

[0202] See Figure 11 , which is the change of the DC bus voltage U dc under different load powers. It can be seen that under the control method of the present invention, when the load suddenly changes at t = 0.5 s and t = 1 s, the DC bus voltage U dc has a smaller overshoot and a shorter steady-state time. The detailed control performance data of the two are shown in Table 4.

[0203] Table 4 Simulation performance comparison of two control methods under load changes

[0204]

[0205] In summary, when the source-load power fluctuates, the control method of the present invention significantly reduces the overshoot and regulation time of the photovoltaic energy storage system compared with the traditional method, and can quickly restore the stability of the bus voltage and power in the photovoltaic energy storage system. Thus, the stable control of the bus voltage and the reasonable distribution of power in the photovoltaic energy storage system are realized, enabling the safe and stable operation of the photovoltaic energy storage system.

[0206] It should be noted that the embodiments of the present invention are preferred embodiments rather than limitations thereof. It should be pointed out that for those of ordinary skill in the art, without departing from the principle of the present invention, modifications can be made to the specific embodiments or equivalent substitutions can be made to some technical features, and all of them should be regarded as falling within the scope of the present invention.

Claims

1. A sliding mode auto-disturbance rejection control method for a photovoltaic and energy storage system considering the power fluctuations of the source and load, characterized in that It includes the following steps: Step S1: Considering the power volatility of the source and load in the energy storage system, analyze the charging and discharging behavior of the battery, construct a mathematical model of the battery - photovoltaic system, and obtain the corresponding state equation. In the energy storage system, the battery is connected to the DC bus through a half - bridge bidirectional Buck / Boost converter. Analyze the charging and discharging behavior of the lithium battery and the topology of the half - bridge bidirectional Buck / Boost converter of the photovoltaic system, construct a mathematical model of the battery - photovoltaic system, and obtain the corresponding state equation. Step S2: Based on the sliding mode control and active disturbance rejection control principles, design the controller structure according to the mathematical model constructed in Step S1, and design the current loop. The specific design of the current loop is as follows: The current loop adopts sliding mode control, and the mathematical model of sliding mode control is: Where, U dc is the DC bus voltage, I L is the inductor current, f(U dc , I L ) is the non-linear relationship between the DC bus voltage and the inductor current, and ω1 is the influence of the optical storage system on the current; Set the sliding mode surface s' of the current loop as: s' = I L -I Lref (6) where s' represents the current loop sliding surface, and I L is the inductor current, and I Lref is the reference value of the inductor current; Design u1 to make the system state tend to the sliding mode surface and stay on it, which is specifically expressed as: where u1 is the corresponding sliding mode control law, and b i is the compensation coefficient, and k i is the main control parameter, and sgn(e) is the sign function; Step S3: Design each part of the voltage loop and introduce it into the controller structure designed in Step S2 to achieve the stable control of the bus voltage of the energy storage system and the reasonable distribution of power when the source - load power fluctuates.

2. The sliding mode active disturbance rejection control method for a photovoltaic and energy storage system considering the power fluctuations of the power generation and load according to claim 1, wherein The analysis of the charging and discharging behavior of the lithium battery, the analysis of the topology of the half - bridge bidirectional Buck / Boost converter of the photovoltaic system, the construction of a mathematical model of the battery - photovoltaic system, and the obtaining of the corresponding state equation are specifically as follows: Step S11: Analyze the charging and discharging behavior of the battery, establish its equivalent circuit model, and obtain the output characteristic equation as: Wherein, U oc is the open-circuit voltage of the battery, U p and U B are the terminal voltages of the RC circuit and the battery respectively, I is the current of the battery, R1, R2 and C are the internal resistance, polarization resistance and polarization capacitance of the battery respectively; Use the ampere - hour integration method to calculate the state of charge of the battery, and obtain the following formula: where SOC(t s ) represents the state of charge of the battery, E Bmax represents the total energy of the battery, t0 and t s are the start time and end time of the integration process respectively, I b represents the output current of the battery. When it is positive, the battery is in a discharging state; otherwise, the battery is in a charging state. Step S12: Analyze the charging and discharging states of the interface circuit of the half - bridge bidirectional Buck / Boost converter of the photovoltaic system, and obtain the equivalent state equation as: Where L is the inductance, C B and C dc are the filter capacitors, U B and U dc are the energy storage side voltage and the DC bus voltage respectively, I B and I L are the energy storage side current and the inductor current respectively, R eq is the equivalent load on the bus side, and u is the DC bus side voltage variable, specifically expressed as: Where U dc is the DC bus voltage, R is the load, and P CPL is the sum of the photovoltaic power generation output power and the power consumed on the DC bus.

3. The sliding mode active disturbance rejection control method for a photovoltaic and energy storage system considering source-load power fluctuations according to claim 1, wherein In Step S3, the design of each part of the voltage loop specifically includes the following steps: Step S31: Design a sliding mode differential estimator. Step S32: Design a sliding mode extended state observer. Step S33: Design an error feedback controller.

4. The sliding mode active disturbance rejection control method for a photovoltaic-storage system considering source-load power fluctuations according to claim 3, wherein In Step S31, the design of the sliding mode differential estimator is specifically: The sliding mode differential estimator model is described by the following differential equation: where x1 is the state variable used to track the DC bus voltage reference value U dcref , x2 is the derivative estimate of the output signal, k is the switching gain used to adjust the strength of the sliding mode differentiation, sgn(e) is the sign function, and U dcref is the DC bus voltage reference value; Define the sliding mode surface s” of the sliding mode differential estimator: s”=x1-U dcref (9) Where s” represents the sliding mode surface of the sliding mode differential estimator. When s” = 0, the system will move on the sliding mode surface, enabling x1 to track U dcref ; Discretize the above - mentioned continuous system to obtain: where \(k_0\) is the switching gain and \(T\) s is the sampling period.

5. The sliding mode active disturbance rejection control method for a photovoltaic and energy storage system considering source-load power fluctuations according to claim 3, characterized in that In Step S32, the design of the sliding mode extended state observer specifically includes the following steps: Step S321: The non - linear function expression of the DC bus voltage input and output is: where L is the inductance, C dc is the filter capacitor, U dc is the DC bus voltage, I L is the inductor current, u is the DC bus side voltage variable, R eq is the equivalent load on the bus side, and ω represents the disturbance received by the system; Define the perturbation function f1(U dc , ω, t) and the control quantity gain b respectively, and their expressions are as follows: In Equation (12), f1(U dc , ω, t) is the perturbation function, and b is the control quantity gain; Rearranging formulas (11) and (12), an expression linearly combined by the system input U dc and the system output I L is obtained: The control quantity gain b is an inherent parameter of the system, and it is difficult to obtain its actual value. Therefore, let b0 be the estimated value of b, and obtain: In the formula, b0 is the estimated value of b; Step S322: Take the state variable x1 = U dc , x2 = f, let the vector x = [x1, x2], and obtain the state - space equation form of the system as follows: Among them, C = [10], D = [0], Let the state vector \(z = [z_1, z_2]\), where the state variable \(z_1\) is used to track the DC bus voltage \(U\). dc , and the state variable \(z_2\) is used to track the total disturbance; the linear extended state observer is expressed in the form of the following state - space equation: where F = [β1, β2] T , and β1 and β2 are the gains of error feedback; Use the pole - placement method and perform Laplace transform to obtain: where ω0 is the bandwidth parameter; I Lref is the reference value of the inductor current; Step S323: The state - space equation of the sliding mode extended state observer is: In the formula, k1, k2 are sliding mode gain parameters, s” represents the sliding mode surface of the sliding mode differential estimator, L0 is the controller gain, and adjust k1, k2 to make the characteristics of the sliding mode extended state observer match Equation (17); According to the error state, design u2 to make the system state tend to the sliding mode surface and stay on it, which is specifically expressed as: where: u2 is the corresponding sliding mode control law, represents the compensation for the total disturbance, k u is the error compensation coefficient, and sgn(e) is the sign function.

6. The sliding mode active disturbance rejection control method for a photovoltaic and energy storage system considering the power fluctuations of the power source and load according to claim 5, wherein, In step S33, the design error feedback controller is specifically as follows: The error feedback controller consists of two parts: a disturbance compensation unit and a proportional control unit. Let u0 be the output of the error feedback controller. Then the implementation form of the disturbance compensation unit is: where, I Lref is the reference value of the inductor current; u0 is the output of the error feedback controller, b0 is the estimated value of the control quantity gain b, and u0 / b0 represents the ideal control signal before disturbance compensation; z2 is the state variable used to track the total disturbance, and the role of -z2 / b0 is to reduce the influence of the total disturbance estimated by the sliding mode extended state observer; After substituting equation (20) into (14) and taking the limit, we get: The system is simplified to a single-integral system. Therefore, a proportional controller is designed as follows: u0 = ω c (x1 - z1)(22) In equations (21) and (22), x1 is the state variable used to track the DC bus voltage reference value U dcref and z1 is the state variable used to track the DC bus voltage U dc , and ω c is the controller gain.

7. A computer storage medium, characterized in that, A computer program is stored on a medium. When the computer program is executed by a processor, the steps of the sliding mode active disturbance rejection control method for a photovoltaic energy storage system considering source-load power fluctuations according to any one of claims 1 to 6 are implemented.

Images