Photovoltaic hybrid energy storage system and control method, device and equipment thereof

Abstract

The invention relates to a photovoltaic hybrid energy storage system and a control method, device and equipment thereof. The method comprises the following steps: acquiring state measurement data, DC bus voltage and a reference instruction; according to the direct current bus voltage and the reference instruction, an improved active disturbance rejection controller is adopted to calculate and obtain a current inner loop control signal; performing parameter identification on the state measurement data by adopting a recursive least square method to obtain an optimal inductance estimation value; according to the state measurement data, the current inner loop control signal and the optimal inductance estimation value, a dead-beat controller is adopted for calculation to obtain an optimal duty ratio signal; generating a control signal according to the optimal duty ratio signal; and controlling the operation of the corresponding energy storage module according to the control signal. According to the method, the optimal duty ratio signal is obtained by successively processing the data through the improved active disturbance rejection controller, the recursive least square method and the deadbeat controller, so that the disturbance estimation precision and the response speed and tracking precision of the output current of the energy storage module are improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of new energy photovoltaic power generation, and particularly relates to a photovoltaic hybrid energy storage system, a control method, device and equipment thereof. BACKGROUND

[0002] Due to the instability and intermittent changes of light conditions, the output power of the new energy photovoltaic power generation system fluctuates greatly, which cannot meet the real-time power demand. In order to solve the mismatching problem between the fluctuation of power generation and the demand of power load, the photovoltaic hybrid energy storage system technology is introduced into the modern power system. The photovoltaic hybrid energy storage system technology is a system integrating photovoltaic power generation and hybrid energy storage technology, aiming to improve the utilization efficiency of renewable energy and power supply reliability. The control method of the photovoltaic hybrid energy storage system is crucial, which functions to adjust the charging and discharging strategy of the hybrid energy storage system in real time, so as to realize the coordinated operation between photovoltaic power generation and the energy storage system, meet the power demand and maximize the energy utilization rate of the system.

[0003] The defects of the existing control method of the photovoltaic hybrid energy storage system are as follows: first, the total disturbance estimation accuracy is insufficient; second, the control method adopts a double closed-loop control strategy, but the current loop inside the double closed-loop control strategy still uses the PI control method, and the response speed of the output current of the energy storage device is difficult to improve; third, if the control method adopts a dead-beat control method based on an accurate mathematical model, the control method is greatly affected by parameter uncertainty. SUMMARY

[0004] The present application provides a photovoltaic hybrid energy storage system and a control method, device and equipment thereof, which are used to solve the technical problems of slow response speed and low accuracy of the existing control method of the photovoltaic hybrid energy storage system.

[0005] In order to achieve the above-mentioned purpose, the present application provides the following technical solutions: On the one hand, a control method of a photovoltaic hybrid energy storage system is provided, comprising the following steps: Obtaining state measurement data of each energy storage module in the photovoltaic hybrid energy storage system, a direct current bus voltage and a reference instruction; Calculating a current inner loop control signal by using an improved active disturbance rejection controller according to the direct current bus voltage and the reference instruction; Performing parameter identification on the state measurement data of each energy storage module by using a recursive least squares method to obtain an optimal inductance estimation value corresponding to the energy storage module; Calculating an optimal duty cycle signal corresponding to the energy storage module by using a dead-beat controller according to the state measurement data of each energy storage module, the current inner loop control signal and the optimal inductance estimation value; The control signal for turning on and off the switch tube of the energy storage module in the photovoltaic hybrid energy storage system is generated according to the optimal duty cycle signal; and the operation of the energy storage module corresponding to the control signal is controlled.

[0006] Preferably, the current inner loop control signal is calculated by using an improved active disturbance rejection controller according to the state measurement data and the reference instruction, and the calculation includes: The estimation error of the state observer in the first-order active disturbance rejection controller, the first error gain and the second error gain are obtained, and the proportional gain, the gain coefficient, the correction time constant and the correction coefficient of the active disturbance rejection controller are obtained; The first observed state vector is calculated according to the DC bus voltage, the estimation error and the first error gain; and the second observed state vector is calculated according to the DC bus voltage, the estimation error and the second error gain; The second observed state vector is corrected in series according to the correction time constant and the correction coefficient to obtain a third observed state vector; The current inner loop control signal is calculated according to the reference instruction, the proportional gain, the gain coefficient, the first observed state vector and the third observed state vector.

[0007] Preferably, the control method of the photovoltaic hybrid energy storage system includes: the current inner loop control signal is calculated by using a disturbance compensation feedback formula according to the reference instruction, the proportional gain, the gain coefficient, the first observed state vector and the third observed state vector; and the disturbance compensation feedback formula is: ; ; ; In the formula, k p is the proportional gain, b 0 is the gain coefficient, t is the time for obtaining the state measurement data, r is the reference instruction at the first time, t is the first observed state vector at the first time, t is the third observed state vector at the first time, z is the current inner loop control signal, t is the second observed state vector at the first time, t is the first observed state vector at the first time, z is the third observed state vector at the first time, t is the current inner loop control signal, t is the second observed state vector at the first time, u is the current inner loop control signal, z is the second observed state vector at the first time, t is the current inner loop control signal, t is the second observed state vector at the first time, Td To correct the time constant, τ For correction factors, z =[ z 1, z 2] T yes[ y , f ] T The observed state vector, e The estimation error of the state observer, l 1 represents the first error gain. l 2 represents the second error gain. y = v bus , v bus This is the DC bus voltage. f The total disturbance for the active disturbance rejection controller. The observed state vector z The derivative of 1, The observed state vector z The derivative of 2, where s is a variable in the complex field of the transfer function. z 3 ( s ) is the transfer function for series correction. z 3 ( t ) is by z 3 ( s Transformed via inverse Laplace transform. z 2 ( s ) is by z 2 ( t It is transformed by Laplace transform.

[0008] Preferably, the recursive least squares method is used to identify parameters in the state measurement data of each energy storage module to obtain the optimal inductance estimate corresponding to the energy storage module, including: Obtain the topology diagram of each energy storage module in the photovoltaic hybrid energy storage system, and construct an inductance parameter identification model corresponding to the energy storage module based on the topology diagram; The inductor parameter identification model is transformed using the general format of the recursive least squares method to obtain an iterative calculation model; Based on the state measurement data of each energy storage module, the recursive algorithm of the recursive least squares method is used to iteratively calculate according to the iterative calculation model until the observation estimation parameters that meet the convergence conditions are obtained. The switching cycle of each energy storage module is obtained, and the optimal inductance estimate corresponding to the energy storage module is calculated based on the observation estimation parameters and the switching cycle corresponding to the energy storage module. The convergence condition is that the observed estimated parameters calculated iteratively remain at a constant value.

[0009] Preferably, the optimal duty cycle signal corresponding to each energy storage module is calculated using a deadbeat controller based on the state measurement data of each energy storage module, the current inner loop control signal, and the optimal inductance estimate. Obtain the cutoff frequency of the energy storage module in the photovoltaic hybrid energy storage system, and calculate the current reference value of each energy storage module based on the current inner loop control signal and the cutoff frequency; The control cycle of the deadbeat controller is obtained, and the optimal duty cycle signal corresponding to the energy storage module is calculated based on the state measurement data, the current reference value, the control cycle, and the optimal inductance estimate of each energy storage module.

[0010] Preferably, the control method of the photovoltaic hybrid energy storage system includes: calculating the optimal duty cycle signal corresponding to each energy storage module using the optimal control duty cycle expression of a deadbeat controller based on the state measurement data, the current reference value, the control cycle, and the optimal inductance estimate of each energy storage module; the optimal control duty cycle expression is: ; In the formula, d For the optimal duty cycle signal, v ( t ) is the first t Terminal voltage of time-based energy storage module L This is the optimal inductance estimate for the energy storage module. t To obtain the time for state measurement data, i ( t ) is the first t Current reference value of time-based energy storage module v bus ( t ) is the first t DC bus voltage over time i ( t ) is the first t The current of the time-based energy storage module T db To control the cycle.

[0011] On another front, a photovoltaic hybrid energy storage system is provided, including a DC bus and a hybrid energy storage module, a photovoltaic array, a DC load, and an AC load connected to the DC bus. The hybrid energy storage module includes a first energy storage module composed of batteries and a second energy storage module composed of capacitors. The hybrid energy storage module is used to obtain a first control signal of the first energy storage module and a second control signal of the second energy storage module according to the control method of the photovoltaic hybrid energy storage system described above, and to control the operation of the first energy storage module according to the first control signal and the operation of the second energy storage module according to the second control signal.

[0012] Preferably, the photovoltaic array is connected in parallel to the DC bus via a first DC-DC converter, and the DC load and the AC load are connected in parallel to the DC bus via a second DC-DC converter, an inverter, and a filter capacitor, respectively.

[0013] On the other hand, a control device for a photovoltaic hybrid energy storage system is provided, including a data acquisition module, a first calculation module, a parameter identification module, a second calculation module, and a control module; The data acquisition module is used to acquire the status measurement data, DC bus voltage and reference commands of each energy storage module in the photovoltaic hybrid energy storage system; The first calculation module is used to calculate the inner current control signal based on the DC bus voltage and the reference command using an improved active disturbance rejection controller. The parameter identification module is used to perform parameter identification on the state measurement data of each energy storage module using the recursive least squares method, so as to obtain the optimal inductance estimate corresponding to the energy storage module. The second calculation module is used to calculate the optimal duty cycle signal corresponding to the energy storage module by using a deadbeat controller based on the state measurement data of each energy storage module, the current inner loop control signal and the optimal inductance estimate. The control module is used to generate control signals for turning on and off the switching transistors of the energy storage modules in the photovoltaic hybrid energy storage system based on the optimal duty cycle signal; and to control the operation of the corresponding energy storage modules based on the control signals.

[0014] On the other hand, a terminal device is provided, including a processor and a memory; The memory is used to store program code and transmit the program code to the processor; The processor is used to execute the control method of the photovoltaic hybrid energy storage system described above according to the instructions in the program code.

[0015] The photovoltaic hybrid energy storage system and its control method, apparatus, and equipment are disclosed. The control method of the photovoltaic hybrid energy storage system includes acquiring the state measurement data, DC bus voltage, and reference command of each energy storage module in the photovoltaic hybrid energy storage system; calculating the inner current control signal using an improved active disturbance rejection controller based on the DC bus voltage and reference command; identifying parameters of the state measurement data of each energy storage module using a recursive least squares method to obtain the optimal inductance estimate corresponding to the energy storage module; calculating the optimal duty cycle signal corresponding to the energy storage module using a deadbeat controller based on the state measurement data, the inner current control signal, and the optimal inductance estimate of each energy storage module; generating control signals for turning on and off the switching transistors of the energy storage modules in the photovoltaic hybrid energy storage system based on the optimal duty cycle signal; and controlling the operation of the corresponding energy storage module based on the control signals.

[0016] As can be seen from the above technical solutions, this application has the following advantages: The control method of the photovoltaic hybrid energy storage system first acquires the state measurement data, DC bus voltage and reference command of each energy storage module in the photovoltaic hybrid energy storage system, and then uses an improved active disturbance rejection controller with series correction, recursive least squares method and deadbeat controller to process the data to obtain the optimal duty cycle signal. This improves the disturbance estimation accuracy, the response speed and tracking accuracy of the energy storage module output current in the process of obtaining the optimal duty cycle signal, reduces the impact of parameter uncertainty in the energy storage module on the control effect, and solves the technical problems of slow response speed and low accuracy in the control methods of existing photovoltaic hybrid energy storage systems.

[0017] The control device of this photovoltaic hybrid energy storage system acquires the state measurement data, DC bus voltage, and reference commands of each energy storage module in the system through a data acquisition module, a first calculation module, a parameter identification module, a second calculation module, and a control module. Then, an improved active disturbance rejection controller with series correction, recursive least squares method, and deadbeat controller are used to process the data to obtain the optimal duty cycle signal. This improves the disturbance estimation accuracy, the response speed and tracking accuracy of the energy storage module output current in the process of obtaining the optimal duty cycle signal, and reduces the impact of parameter uncertainty in the energy storage module on the control effect. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is a flowchart illustrating the steps of the control method for the photovoltaic hybrid energy storage system described in the embodiments of this application; Figure 2 This is a schematic diagram of the control structure of the photovoltaic hybrid energy storage system control method described in the embodiments of this application; Figure 3 This is a schematic diagram of the topology of the photovoltaic hybrid energy storage system described in the embodiments of this application; Figure 4 This is a schematic diagram of the control device of the photovoltaic hybrid energy storage system described in the embodiments of this application; Figure 5 This is a schematic diagram of the terminal device described in an embodiment of this application. Detailed Implementation

[0020] To make the inventive objectives, features, and advantages of this application more apparent and understandable, the technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the embodiments described below are only some embodiments of this application, and not all embodiments. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0021] In the description of the embodiments of this application, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of the embodiments of this application, "multiple" means two or more, unless otherwise explicitly specified.

[0022] In the embodiments of this application, unless otherwise explicitly specified and limited, the terms "installation," "connection," "linking," "fixing," etc., should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components. Those skilled in the art can understand the specific meaning of the above terms in the embodiments of this application according to the specific circumstances.

[0023] This application provides a photovoltaic hybrid energy storage system and its control method, apparatus and equipment, which solves the technical problems of slow response speed and low accuracy in the control methods of existing photovoltaic hybrid energy storage systems.

[0024] Example 1: Figure 1 This is a flowchart illustrating the steps of the control method for the photovoltaic hybrid energy storage system described in the embodiments of this application. Figure 2This is a schematic diagram of the control structure of the photovoltaic hybrid energy storage system control method described in the embodiments of this application. Figure 3 This is a schematic diagram of the topology of the photovoltaic hybrid energy storage system described in the embodiments of this application.

[0025] like Figure 1 and Figure 2 As shown in the figure, this application provides a control method for a photovoltaic hybrid energy storage system, including the following steps: S1. Acquire the status measurement data, DC bus voltage, and reference commands of each energy storage module in the photovoltaic hybrid energy storage system.

[0026] It should be noted that step S1 involves acquiring the data required to control the operation of each energy storage module, providing data for subsequent steps. In this embodiment, the reference instruction is the reference instruction for the control signal of the inner current loop. The reference instruction can be understood as a reference signal, which can be understood as an input signal of the controller in the photovoltaic hybrid energy storage system, and the desired output signal of the controller.

[0027] like Figure 3 As shown in this embodiment, the photovoltaic hybrid energy storage system includes a DC bus and a hybrid energy storage module, a photovoltaic array, a DC load, and an AC load connected to the DC bus. The hybrid energy storage module includes a first energy storage module composed of batteries and a second energy storage module composed of capacitors. The hybrid energy storage module is used to obtain a first control signal of the first energy storage module according to the control method of the photovoltaic hybrid energy storage system. q bm The second control signal of the second energy storage module q sc According to the first control signal q bm Control the operation of the first energy storage module according to the second control signal q sc Control the operation of the second energy storage module.

[0028] It should be noted that, as Figure 3 As shown, the first energy storage module is connected to the DC bus via a first bidirectional DC-DC converter, enabling bidirectional power flow. The second energy storage module is connected to the DC bus via a second bidirectional DC-DC converter, allowing it to absorb or output power from the DC bus. Both the first and second bidirectional DC-DC converters include an inductor L, a first power switch S1, and a second power switch S2. The DC bus voltage is obtained using a voltage sensor. v bus The current output of the first energy storage module is obtained through a current sensor. i bmThe terminal voltage of the first energy storage module is obtained through a voltage sensor. v bm The current output of the second energy storage module is obtained through a current sensor. i sc The terminal voltage of the second energy storage module is obtained through a voltage sensor. v sc .in, bm This indicates the first energy storage module. sc This refers to the second energy storage module. In this embodiment, the hybrid energy storage module consists of a first energy storage module composed of batteries and a second energy storage module composed of capacitors. Compared to a single energy storage module, the advantage of the hybrid energy storage module lies in combining the complementary energy storage characteristics of batteries and supercapacitors. Because current technology offers high energy density but low power density for batteries, and high power density but low energy density for supercapacitors, the hybrid energy storage module provides functionality close to an ideal energy storage system. Wherein, if q This represents the switching signal of the first power switch S1. q The inverted signal represents the switching signal of the second power switch S2, which controls the signal. The state measurement data of the first energy storage module includes the terminal voltage. v bm and current i bm The status measurement data of the second energy storage module includes terminal voltage. v sc and current i sc .

[0029] like Figure 3 As shown in the embodiment of this application, the photovoltaic array is connected in parallel to the DC bus through a first DC-DC converter, and the DC load and AC load are connected in parallel to the DC bus through a second DC-DC converter, an inverter and a filter capacitor C, respectively.

[0030] It should be noted that the photovoltaic array inputs the electrical energy generated by the photovoltaic array in real time to the DC bus through the first DC-DC converter. Figure 3 In v pv and i pv These represent the terminal voltage and photovoltaic current of the photovoltaic array, respectively. The DC load and AC load are connected to the DC bus via the second DC-DC converter and inverter, respectively. The total load current they form is defined as... i load The DC bus voltage is obtained by measuring the DC bus voltage using a voltage sensor. v bus To smooth out fluctuations in the bus voltage, a filter capacitor C connected in parallel with the DC bus was used.

[0031] In this embodiment, the control method of the photovoltaic hybrid energy storage system adjusts the power output of the first and second energy storage modules in real time through the obtained control signals to achieve photovoltaic power generation absorption and maintain the stability of the DC bus voltage. Since the energy storage modules are connected to the DC bus via bidirectional DC-DC converters, mathematical models of the bidirectional DC-DC converters for the first and second energy storage modules can be established separately. Furthermore, since the subsequent deadbeat controller design only utilizes inductance parameters, only an inductance parameter model needs to be established here. The expression for the inductance parameter model is as follows: ; ; From the expression of the inductor parameter model, it can be seen that through the duty cycle signal d bm Control the operation of the first energy storage module to output power and control duty cycle signals. d sc To control the operation of the second energy storage module for power output, the optimal duty cycle signal needs to be obtained through the control method of this photovoltaic hybrid energy storage system. d bm and optimal duty cycle signal d sc .

[0032] S2. Based on the DC bus voltage and reference command, an improved active disturbance rejection controller is used to calculate and obtain the inner loop current control signal.

[0033] It should be noted that in step S2, the DC bus voltage obtained in step S1 is used. v bus and reference instructions r The improved active disturbance rejection controller is used to calculate and obtain the inner current control signal. u This provides data for obtaining the control signal q of the photovoltaic hybrid energy storage system. The control method of this photovoltaic hybrid energy storage system improves the traditional active disturbance rejection controller (ADRC) by using a series correction method. The improved ADRC processes the state measurement data and improves the disturbance observation channel of the ADRC. Without losing closed-loop stability, the overall disturbance estimation accuracy of the improved ADRC is improved, thereby improving the accuracy of obtaining the inner current control signal.

[0034] S3. The recursive least squares method is used to identify the parameters of the state measurement data of each energy storage module to obtain the optimal inductance estimate corresponding to the energy storage module.

[0035] It should be noted that in step S3, the recursive least squares method is used to process the state measurement data of each energy storage module obtained in step S1 to obtain the optimal inductance estimate corresponding to the energy storage module, providing data for obtaining the control signal for controlling the operation of the energy storage module. The control method of this photovoltaic hybrid energy storage system uses the recursive least squares method to identify the inductance value of the DC-DC converter in the energy storage module online, providing the subsequent step of using a deadbeat controller to obtain the optimal inductance estimate of the energy storage module in real time, reducing the impact of parameter uncertainty in obtaining the optimal duty cycle signal on the control effect.

[0036] S4. Based on the state measurement data, current inner loop control signal and optimal inductance estimate of each energy storage module, a deadbeat controller is used to calculate the optimal duty cycle signal corresponding to the energy storage module.

[0037] It should be noted that in step S4, the optimal duty cycle signal corresponding to the energy storage module is obtained by processing the state measurement data of each energy storage module obtained in step S1, the current inner loop control signal obtained in step S2, and the optimal inductance estimate obtained in step S3 using a deadbeat controller. This photovoltaic hybrid energy storage system control method replaces the PI control current inner loop design in the existing energy storage system's improved traditional dual-closed-loop control strategy with a deadbeat controller. This allows for the acquisition of the optimal duty cycle signal of the energy storage module to control its operation, enhancing the response speed and tracking accuracy of the energy storage module's output current.

[0038] S5. Generate control signals for turning on and off the switching transistors of the energy storage modules in the photovoltaic hybrid energy storage system based on the optimal duty cycle signal; control the operation of the corresponding energy storage modules based on the control signals.

[0039] It should be noted that in step S5, the mature pulse width modulation technology is used to generate the control signal for turning on and off the switch tube from the optimal duty cycle signal obtained in step S4, and the operation of the corresponding energy storage module is controlled according to the control signal a.

[0040] In this embodiment, the control method of the photovoltaic hybrid energy storage system first acquires the state measurement data, DC bus voltage, and reference command of each energy storage module in the photovoltaic hybrid energy storage system. Then, it uses an improved active disturbance rejection controller with series correction, recursive least squares method, and deadbeat controller to process the data to obtain the optimal duty cycle signal. This improves the disturbance estimation accuracy, the response speed and tracking accuracy of the energy storage module output current in the process of obtaining the optimal duty cycle signal, and reduces the impact of parameter uncertainty in the energy storage module on the control effect.

[0041] This application provides a control method for a photovoltaic hybrid energy storage system, comprising: acquiring state measurement data, DC bus voltage, and reference commands for each energy storage module in the photovoltaic hybrid energy storage system; calculating a current inner loop control signal using an improved active disturbance rejection controller based on the DC bus voltage and reference commands; performing parameter identification on the state measurement data of each energy storage module using a recursive least squares method to obtain an optimal inductance estimate corresponding to the energy storage module; calculating an optimal duty cycle signal corresponding to the energy storage module using a deadbeat controller based on the state measurement data, current inner loop control signal, and optimal inductance estimate of each energy storage module; generating a control signal for turning on and off the switching transistors of the energy storage modules in the photovoltaic hybrid energy storage system based on the optimal duty cycle signal; and controlling the operation of the corresponding energy storage module based on the control signal. The control method of this photovoltaic hybrid energy storage system first acquires the state measurement data, DC bus voltage, and reference command of each energy storage module in the photovoltaic hybrid energy storage system. Then, it uses an improved active disturbance rejection controller with series correction, recursive least squares method, and deadbeat controller to process the data to obtain the optimal duty cycle signal. This improves the disturbance estimation accuracy, the response speed and tracking accuracy of the energy storage module output current in the process of obtaining the optimal duty cycle signal, reduces the impact of parameter uncertainty in the energy storage module on the control effect, and realizes the control of the photovoltaic hybrid energy storage system. This solves the technical problems of slow response speed and low accuracy in the existing control methods of photovoltaic hybrid energy storage systems.

[0042] In one embodiment of this application, the current inner loop control signal is calculated using an improved active disturbance rejection controller based on state measurement data and reference commands, including: Obtain the estimation error, first error gain, and second error gain of the state observer in the first-order active disturbance rejection controller, and obtain the proportional gain, gain coefficient, correction time constant, and correction coefficient of the active disturbance rejection controller; The first observation state vector is obtained by calculating the DC bus voltage, estimation error, and first error gain; the second observation state vector is obtained by calculating the DC bus voltage, estimation error, and second error gain. The second observation state vector is cascaded and corrected based on the correction time constant and correction coefficient to obtain the third observation state vector; The current inner loop control signal is calculated based on the reference command, proportional gain, gain coefficient, first observation state vector, and third observation state vector. The inner current control signal is calculated using a disturbance compensation feedback formula based on the reference command, proportional gain, gain coefficient, first observed state vector, and third observed state vector. The disturbance compensation feedback formula is as follows: ; ; ; In the formula, k p For proportional gain, b 0 represents the gain coefficient. t To obtain the time for state measurement data, r ( t ) is the first t Time reference instructions, z 1 ( t ) is the first t The first observed state vector in time, z 3 ( t ) is the first t The third observation state vector in time, u This is the inner loop control signal for the current. z 2 ( t ) is the first t The second observation state vector in time, T d To correct the time constant, τ For correction factors, z =[ z 1, z 2] T yes[ y , f ] T The observed state vector, e The estimation error of the state observer, l 1 represents the first error gain. l 2 represents the second error gain. y = v bus , v bus This is the DC bus voltage. f The total disturbance for the active disturbance rejection controller. The observed state vector z The derivative of 1, The observed state vector z The derivative of 2, where s is a variable in the complex field of the transfer function. z 3 ( s ) is the transfer function for series correction. z 3 ( t ) is by z 3 ( s Transformed via inverse Laplace transform. z 2 ( s ) is by z 2 ( t It is transformed by Laplace transform.

[0043] It should be noted that by using a first-order active disturbance rejection controller (ADRC), the controlled photovoltaic hybrid energy storage system is abstracted into an ADRC. The ADRC only needs to acquire the tracking signal of the control command for feedback control, avoiding the introduction of a tracking differentiator. It simplifies the control structure by requiring only the design of an extended state observer (ESO) and a feedback control law. In this case, the ADRC is easy to implement and has fewer control parameters. The current inner loop control signal is defined as... u ,Right now u = i tot ; y The output of the photovoltaic hybrid energy storage system, i.e. y = v bus Based on the fundamental control concept of a first-order Active Disturbance Rejection Controller (ADRC), Equation 1 holds, which is: Equation 1 shows that the main factors affecting the dynamic change of the DC bus voltage are the inner current loop control signal and the total disturbance. In this embodiment, the first error gain of the first-order active disturbance rejection controller... l 1=2 ω o The second error gain of the first-order active disturbance rejection controller l 2= ω o 2 . ω o This represents the bandwidth of the state observer ESO of the first-order active disturbance rejection controller. z 2. It can converge and track the total disturbance of the photovoltaic hybrid energy storage system at a relatively fast speed. f .

[0044] In the embodiments of this application, because It can be seen that the transfer function of the first-order active disturbance rejection controller from the total disturbance to the disturbance observation is... for: ; In the formula, F ( s Let be the transfer function of the total disturbance, where s For the field of complex numbers s。

[0045] In the embodiments of this application, the improved active disturbance rejection controller (iLADRC) is obtained based on the series correction of the first-order active disturbance rejection controller. To improve the disturbance estimation accuracy of the improved active disturbance rejection controller (iLADRC), the concept of series correction is applied, and the total disturbance in the improved active disturbance rejection controller (iLADRC) is recorrected to... z 3 ( t Its transfer function is z 3 ( tThe final total disturbance estimate that enters the compensation control. f No longer z 2 ( t (not) but corrected z 3 ( t The improved state observer ESO structure of the iLADRC (Automatic Disturbance Rejection Controller) is transformed into a third-order state-space equation, which is expressed as: ; Compared with the existing first-order active disturbance rejection controller TLADRC, the improved active disturbance rejection controller iLADRC has a higher disturbance estimation error. E iL_f The disturbance estimation error compared to the existing first-order active disturbance rejection controller TLADRC E TL_f The transfer functions are as follows: ; ; In the formula, F ( s Let be the transfer function of the total disturbance, where s For the field of complex numbers s Based on the slope K r The steady-state error under ramp input can be used to obtain the final value of the improved active disturbance rejection controller iLADRC by combining the Laplace transform. e iL_f The final value of the existing first-order active disturbance rejection controller TLADRC e TL_f The formula for the Laplace transform is: ; ; This comparison shows that the first-order active disturbance rejection controller TLADRC has a non-zero total disturbance estimation error, while the improved active disturbance rejection controller iLADRC satisfies... ω o T d (1- τ Setting the parameter to 2 can eliminate steady-state error, thereby improving the estimation accuracy of disturbances and enabling the improved active disturbance rejection controller to have better anti-interference performance.

[0046] In one embodiment of this application, the recursive least squares method is used to identify parameters of the state measurement data of each energy storage module to obtain the optimal inductance estimate corresponding to the energy storage module, including: Obtain the topology diagram of each energy storage module in the photovoltaic hybrid energy storage system, and construct an inductance parameter identification model corresponding to the energy storage module based on the topology diagram. The inductor parameter identification model is transformed using the general format of recursive least squares method to obtain an iterative calculation model; Based on the state measurement data of each energy storage module, the recursive algorithm of the recursive least squares method is used to iteratively calculate according to the iterative calculation model until the observation estimation parameters that meet the convergence conditions are obtained. The switching cycle of each energy storage module is obtained, and the optimal inductance estimate corresponding to the energy storage module is calculated based on the observed estimation parameters and switching cycle corresponding to the energy storage module. The convergence condition is that the observed estimated parameters calculated iteratively remain at a constant value.

[0047] It should be noted that the duty cycle control signal of the deadbeat controller in the inner current loop needs to obtain the optimal inductance estimate of the first energy storage module. L bm Optimal inductance estimate of the second energy storage module L sc In the actual operation of a bidirectional DC-DC converter, the inductance changes with the converter's operating conditions. Furthermore, heat accumulation and uneven magnetic field variations during prolonged use can cause the inductance value to deviate from its rated value, leading to parameter uncertainty. Because the recursive least squares method has advantages such as fast calculation and convergence speed and low computational cost, this photovoltaic hybrid energy storage system's control method employs online parameter identification using the recursive least squares method to estimate the optimal inductance value for the first energy storage module. L bm Optimal inductance estimate of the second energy storage module L sc Real-time parameter estimation is used to improve the deadbeat controller.

[0048] In the embodiments of this application, according to as follows Figure 3 The state equations for the topology diagram of each energy storage module in the photovoltaic hybrid energy storage system shown are expressed as follows: ; ; In the formula, parentheses ( )middle k Indicates the first k One switching cycle; v bm ( k ), i bm ( k )and v sc( k ), i sc ( k These are the terminal voltage and output current of the first energy storage module and the terminal voltage and output current of the second energy storage module, respectively. d bm ( k )and d sc ( k ) are respectively the first k The duty cycle signal output in each switching cycle; T s Let be the switching cycle of the switching transistor. The parameter identification model is obtained by transforming the state equation. The expression of the parameter identification model is: ; ; Expressions in a general format In the formula, ξ ( k ) represents the model residuals. θ ( k ) is the required observation parameter. T ( k ) represents the observation vector. y ( k ( ) represents the measured value. The expression for the iterative calculation model is: ; ; The expression for the recursive algorithm of recursive least squares is: ; In the formula, K ( k )and P ( k These are the gain matrix and covariance matrix, respectively, with initial values... P (0) is generally taken as 10 α I, where I is the identity matrix. α λ is a large positive integer; λ is the forgetting factor, which is usually taken as λ=1. for θ ( k The estimated value of ). According to the recursive algorithm, the core of recursive least squares lies in combining the observation vector. T ( k ), measured values y ( k ) and gain matrix K ( k ), for the previous switching cycle The estimated value is then corrected. After multiple rounds of correction, the estimated value can quickly converge to a satisfactory level of accuracy. And because of the switching cycle T s It is known that by applying the recursive algorithm to the expressions of the iterative calculation model, the optimal inductance estimates of the bidirectional DC-DC converters in the first and second energy storage modules can be obtained. L bm and optimal inductance estimate L sc This provides accurate model parameters for the deadbeat controller. The recursive algorithm is simply a general formula; each expression of the iteratively calculated model is plugged into the recursive algorithm for iterative calculation, thereby solving for the observed estimated parameters. θ bm and observation estimated parameters θ sc The estimated value. For example... θ bm ( k The estimated value of ) = θ bm ( k -1) estimated value + K ( k )[ y bm ( k )- bm T ( k ) θ bm ( k The estimated value of -1).

[0049] In one embodiment of this application, the optimal duty cycle signal corresponding to the energy storage module is obtained by using a deadbeat controller to calculate based on the state measurement data of each energy storage module, the current inner loop control signal, and the optimal inductance estimate. Obtain the cutoff frequency of the energy storage module in the photovoltaic hybrid energy storage system, and calculate the current reference value of each energy storage module based on the current inner loop control signal and the cutoff frequency; The control cycle of the deadbeat controller is obtained, and the optimal duty cycle signal corresponding to the energy storage module is calculated based on the state measurement data, current reference value, control cycle and optimal inductance estimate of each energy storage module. Specifically, the optimal control duty cycle signal corresponding to each energy storage module is calculated using the optimal control duty cycle expression of the deadbeat controller based on the state measurement data, current reference value, control cycle, and optimal inductance estimate of each energy storage module. The optimal control duty cycle expression is as follows: ; In the formula, d For the optimal duty cycle signal, v ( t ) is the first t Terminal voltage of time-based energy storage module L This is the optimal inductance estimate for the energy storage module. t To obtain the time for state measurement data, i ( t ) is the first t Current reference value of time-based energy storage module v bus ( t ) is the first t DC bus voltage over time i ( t ) is the first t The current of the time-based energy storage module T db To control the cycle.

[0050] It should be noted that, given the high energy density of batteries and the high power density of supercapacitors, a low-pass filter (LPF) is chosen to fully utilize their respective energy storage advantages, and the total required current reference value is [not specified]. i tot Power distribution is performed, wherein the inner current loop control signal is: u = i tot The current reference value of the first energy storage module in this photovoltaic hybrid energy storage system. i bm The current reference value of the second energy storage module in this photovoltaic hybrid energy storage system can be calculated using the first power allocation formula. i sc The power allocation can be calculated using the second power allocation formula. The first power allocation formula is: ; The second power allocation formula is: ; In the formula, ω cutThe cutoff frequency of the low-pass filter is determined by the response speed of the first energy storage module. According to the first and second power allocation formulas, the first energy storage module is responsible for the average power output to maintain the average energy balance of the photovoltaic hybrid energy storage system; while the second energy storage module is responsible for responding to instantaneous power demands, quickly absorbing or outputting high-frequency power to improve the response capability of the photovoltaic hybrid energy storage system. Based on the first and second power allocation formulas, the optimal duty cycle signal of the first energy storage module in the deadbeat controller can be derived. d bm The expression for the optimal duty cycle signal of the second energy storage module d sc The expression for the optimal duty cycle signal. d bm The expression and optimal duty cycle signal d sc The expressions are as follows: ; ; From the expression d bm and expression d sc It can be seen that, T db This refers to the controller's control cycle. Because it achieves the optimal control duty cycle in each control cycle, compared to traditional PI control, the deadbeat controller eliminates inertial lag and can quickly adjust the output of the photovoltaic hybrid energy storage system based on its current state, maintaining power balance between the photovoltaic system and the load.

[0051] Example 2: Figure 4 This is a schematic diagram of the control device of the photovoltaic hybrid energy storage system described in the embodiments of this application.

[0052] like Figure 4 As shown in the figure, this application provides a control device for a photovoltaic hybrid energy storage system, including a data acquisition module 10, a first calculation module 20, a parameter identification module 30, a second calculation module 40, and a control module 50; Data acquisition module 10 is used to acquire status measurement data, DC bus voltage and reference commands of each energy storage module in the photovoltaic hybrid energy storage system; The first calculation module 20 is used to calculate the inner current control signal based on the DC bus voltage and reference command using an improved active disturbance rejection controller. The parameter identification module 30 is used to identify the parameters of the state measurement data of each energy storage module using the recursive least squares method, and obtain the optimal inductance estimate corresponding to the energy storage module. The second calculation module 40 is used to calculate the optimal duty cycle signal corresponding to the energy storage module based on the state measurement data of each energy storage module, the current inner loop control signal and the optimal inductance estimate using a deadbeat controller. The control module 50 is used to generate control signals for turning on and off the switching tubes of the energy storage modules in the photovoltaic hybrid energy storage system based on the optimal duty cycle signal; and to control the operation of the corresponding energy storage modules based on the control signals.

[0053] It should be noted that the content of the modules in the device of Embodiment 2 has been described in the steps of the method of Embodiment 1, and the content of the control device module of the photovoltaic hybrid energy storage system will not be repeated in this embodiment. In this embodiment, the control device of the photovoltaic hybrid energy storage system acquires the state measurement data, DC bus voltage and reference command of each energy storage module in the photovoltaic hybrid energy storage system through a data acquisition module, a first calculation module, a parameter identification module, a second calculation module and a control module. Then, an improved active disturbance rejection controller with series correction, recursive least squares method and deadbeat controller are used to process the data to obtain the optimal duty cycle signal, which improves the disturbance estimation accuracy, the response speed and tracking accuracy of the energy storage module output current in the process of obtaining the optimal duty cycle signal, and reduces the impact of parameter uncertainty in the energy storage module on the control effect.

[0054] Example 3: Figure 5 This is a schematic diagram of the terminal device described in an embodiment of this application.

[0055] like Figure 5 As shown, this application provides a terminal device, including a processor and a memory; Memory is used to store program code and transfer the program code to the processor; The processor is used to execute the control method of the photovoltaic hybrid energy storage system described above according to the instructions in the program code.

[0056] It should be noted that the processor is used to execute the steps in the above-described embodiment of a control method for a photovoltaic hybrid energy storage system according to the instructions in the program code. Alternatively, when the processor executes the computer program, it implements the functions of each module / unit in the above-described system / device embodiments.

[0057] For example, a computer program can be divided into one or more modules / units, one or more of which are stored in memory and executed by a processor to complete this application. One or more modules / units can be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of the computer program in a terminal device.

[0058] Terminal devices can be computing devices such as desktop computers, laptops, handheld computers, and cloud servers. Terminal devices may include, but are not limited to, processors and memory. Those skilled in the art will understand that this does not constitute a limitation on the terminal device, which may include more or fewer components than illustrated, or combinations of certain components, or different components. For example, a terminal device may also include input / output devices, network access devices, buses, etc.

[0059] The processor referred to can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor.

[0060] Memory can be an internal storage unit of a terminal device, such as a hard drive or RAM. Memory can also be an external storage device, such as a plug-in hard drive, SmartMedia Card (SMC), Secure Digital (SD) card, or Flash Card. Furthermore, memory can include both internal and external storage units. Memory is used to store computer programs and other programs and data required by the terminal device. Memory can also be used to temporarily store data that has been output or will be output.

[0061] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0062] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection between apparatuses or units through some interfaces, and may be electrical, mechanical, or other forms.

[0063] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0064] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0065] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0066] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A control method for a photovoltaic hybrid energy storage system, characterized in that, Includes the following steps: Acquire status measurement data, DC bus voltage, and reference commands for each energy storage module in the photovoltaic hybrid energy storage system; Based on the DC bus voltage and the reference command, an improved active disturbance rejection controller is used to calculate and obtain the inner loop current control signal; The recursive least squares method is used to identify the parameters of the state measurement data of each energy storage module to obtain the optimal inductance estimate corresponding to the energy storage module. Based on the state measurement data of each energy storage module, the current inner loop control signal and the optimal inductance estimate, a deadbeat controller is used to calculate the optimal duty cycle signal corresponding to the energy storage module. Based on the optimal duty cycle signal, a control signal is generated to control the on and off of the switching transistors of the energy storage modules in the photovoltaic hybrid energy storage system; and the operation of the corresponding energy storage modules is controlled based on the control signal.

2. The control method for the photovoltaic hybrid energy storage system according to claim 1, characterized in that, Based on the state measurement data and the reference command, an improved active disturbance rejection controller is used to calculate the inner current control signal, which includes: The estimation error, first error gain, and second error gain of the state observer in the first-order active disturbance rejection controller are obtained, as are the proportional gain, gain coefficient, correction time constant, and correction coefficient of the active disturbance rejection controller. A first observation state vector is calculated based on the DC bus voltage, the estimation error, and the first error gain; a second observation state vector is calculated based on the DC bus voltage, the estimation error, and the second error gain. The second observation state vector is cascaded and corrected according to the correction time constant and the correction coefficient to obtain the third observation state vector; The current inner loop control signal is calculated based on the reference command, the proportional gain, the gain coefficient, the first observation state vector, and the third observation state vector.

3. The control method for the photovoltaic hybrid energy storage system according to claim 2, characterized in that, include: The current inner loop control signal is calculated using the disturbance compensation feedback formula based on the reference command, the proportional gain, the gain coefficient, the first observed state vector, and the third observed state vector; the disturbance compensation feedback formula is: ； ； ； In the formula, k p For proportional gain, b 0 represents the gain coefficient. t To obtain the time for state measurement data, r ( t ) is the first t Time reference instructions, z 1 ( t ) is the first t The first observed state vector in time, z 3 ( t ) is the first t The third observation state vector in time, u This is the inner loop control signal for the current. z 2 ( t ) is the first t The second observation state vector in time, T d To correct the time constant, τ For correction factors, z =[ z 1, z 2] T yes[ y , f ] T The observed state vector, e The estimation error of the state observer, l 1 represents the first error gain. l 2 represents the second error gain. y = v bus , v bus This is the DC bus voltage. f The total disturbance for the active disturbance rejection controller. The observed state vector z The derivative of 1, The observed state vector z The derivative of 2, where s is a variable in the complex field of the transfer function. z 3 ( s ) is the transfer function for series correction. z 3 ( t ) is by z 3 ( s Transformed via inverse Laplace transform. z 2 ( s ) is by z 2 ( t It is transformed by Laplace transform.

4. The control method for the photovoltaic hybrid energy storage system according to claim 1, characterized in that, The recursive least squares method is used to identify parameters in the state measurement data of each energy storage module, and the optimal inductance estimate corresponding to the energy storage module is obtained, including: Obtain the topology diagram of each energy storage module in the photovoltaic hybrid energy storage system, and construct an inductance parameter identification model corresponding to the energy storage module based on the topology diagram; The inductor parameter identification model is transformed using the general format of the recursive least squares method to obtain an iterative calculation model; Based on the state measurement data of each energy storage module, the recursive algorithm of the recursive least squares method is used to iteratively calculate according to the iterative calculation model until the observation estimation parameters that meet the convergence conditions are obtained. The switching cycle of each energy storage module is obtained, and the optimal inductance estimate corresponding to the energy storage module is calculated based on the observation estimation parameters and the switching cycle corresponding to the energy storage module. The convergence condition is that the observed estimated parameters calculated iteratively remain at a constant value.

5. The control method for the photovoltaic hybrid energy storage system according to claim 1, characterized in that, Based on the state measurement data of each energy storage module, the current inner loop control signal, and the optimal inductance estimate, a deadbeat controller is used to calculate the optimal duty cycle signal corresponding to each energy storage module, including: Obtain the cutoff frequency of the energy storage module in the photovoltaic hybrid energy storage system, and calculate the current reference value of each energy storage module based on the current inner loop control signal and the cutoff frequency; The control cycle of the deadbeat controller is obtained, and the optimal duty cycle signal corresponding to the energy storage module is calculated based on the state measurement data, the current reference value, the control cycle, and the optimal inductance estimate of each energy storage module.

6. The control method for the photovoltaic hybrid energy storage system according to claim 5, characterized in that, include: Based on the state measurement data, current reference value, control cycle, and optimal inductance estimate of each energy storage module, the optimal control duty cycle expression of the deadbeat controller is used to calculate the optimal duty cycle signal corresponding to the energy storage module; the optimal control duty cycle expression is: ； In the formula, d For the optimal duty cycle signal, v ( t ) is the first t Terminal voltage of time-based energy storage module L This is the optimal inductance estimate for the energy storage module. t To obtain the time for state measurement data, i ( t ) is the first t Current reference value of time-based energy storage module v bus ( t ) is the first t DC bus voltage over time i ( t ) is the first t The current of the time-based energy storage module T db To control the cycle.

7. A photovoltaic hybrid energy storage system, characterized in that, The system includes a DC bus and a hybrid energy storage module, a photovoltaic array, a DC load, and an AC load connected to the DC bus. The hybrid energy storage module includes a first energy storage module composed of batteries and a second energy storage module composed of capacitors. The hybrid energy storage module is used to obtain a first control signal for the first energy storage module and a second control signal for the second energy storage module according to the control method of the photovoltaic hybrid energy storage system as described in any one of claims 1-6. The module controls the operation of the first energy storage module according to the first control signal and controls the operation of the second energy storage module according to the second control signal.

8. The photovoltaic hybrid energy storage system according to claim 7, characterized in that, The photovoltaic array is connected in parallel to the DC bus via a first DC-DC converter, and the DC load and the AC load are connected in parallel to the DC bus via a second DC-DC converter, an inverter, and a filter capacitor, respectively.

9. A control device for a photovoltaic hybrid energy storage system, characterized in that, include: The system comprises a data acquisition module, a first calculation module, a parameter identification module, a second calculation module, and a control module. The data acquisition module is used to acquire the status measurement data, DC bus voltage and reference commands of each energy storage module in the photovoltaic hybrid energy storage system; The first calculation module is used to calculate the inner current control signal based on the DC bus voltage and the reference command using an improved active disturbance rejection controller. The parameter identification module is used to perform parameter identification on the state measurement data of each energy storage module using the recursive least squares method, so as to obtain the optimal inductance estimate corresponding to the energy storage module. The second calculation module is used to calculate the optimal duty cycle signal corresponding to the energy storage module by using a deadbeat controller based on the state measurement data of each energy storage module, the current inner loop control signal and the optimal inductance estimate. The control module is used to generate control signals for turning on and off the switching transistors of the energy storage modules in the photovoltaic hybrid energy storage system based on the optimal duty cycle signal; and to control the operation of the corresponding energy storage modules based on the control signals.

10. A terminal device, characterized in that, Including the processor and memory; The memory is used to store program code and transmit the program code to the processor; The processor is configured to execute the control method of the photovoltaic hybrid energy storage system as described in any one of claims 1-6 according to the instructions in the program code.

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