A control method of a direct current converter for a wind-solar dual storage microgrid

Abstract

The present application relates to the technical field of micro-grid dual energy storage system control, and particularly relates to a control method for a DC converter of a wind-solar dual storage micro-grid, which proposes a dual closed-loop converter control, uses a linear quadratic regulator for current inner loop control, and uses a sliding mode control for voltage outer loop control. In the control of the operation mode of a boost-buck converter, a four-switch switching circuit is triggered by the polarity of the power deviation, so as to realize stable and fast switching of energy storage charging and discharging. The system control has less overshoot, and has better robustness and anti-disturbance. In the operation process of the micro-grid dual energy storage system, when either or both of the power fluctuation of the power supply end and the power fluctuation of the load demand end are large, the system can still operate stably when the charging and discharging circuit needs to be switched.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of micro-grid dual energy storage system control, and particularly relates to a control method of a DC converter for a wind-solar dual storage micro-grid. BACKGROUND

[0002] In recent years, clean energy represented by wind energy and solar energy has developed rapidly. With the aggravation of environmental pollution and the exhaustion of traditional energy, the replacement of secondary energy by traditional fuel is imminent. Wind power and solar power have become the most commercially potential and most dynamic renewable energy due to their clean use, low cost and inexhaustible advantages.

[0003] However, wind power and solar power are also facing many problems. First, wind power generation has intermittency and instability, and the power generation is difficult to predict and extremely unstable. When the wind speed is too low or too high, the wind turbine may not operate normally, and if it is connected to the grid, it will cause a great impact on the grid, resulting in a series of problems such as grid voltage fluctuation.

[0004] Similarly, photovoltaic power generation also has the problems of intermittency and uncertainty, and the photoelectric conversion efficiency of the photovoltaic panel is very limited. In the off-grid system of ordinary wind-solar storage micro-grid, a storage battery and a bidirectional DC / DC converter or a storage battery, a super capacitor and a bidirectional DC / DC converter are generally used to complete the throughput of the bus power. The above two systems cannot be separated from the bidirectional DC / DC converter. In actual use, the bidirectional DC / DC converter faces the following problems:

[0005] 1. High circuit complexity and difficult control. The bidirectional DC / DC converter has a more complex circuit, more power devices, control circuit and protection circuit, which requires more delicate control strategy;

[0006] 2. Low efficiency. Although the bidirectional DC / DC converter can work in two directions, its overall efficiency is lower than that of the unidirectional converter. Especially under light load conditions, the efficiency decreases more obviously. Especially when the switching frequency is high, the loss is more obvious;

[0007] 3. Electromagnetic interference. Since the bidirectional DC / DC converter needs to switch power frequently, it is more prone to electromagnetic interference. Therefore, in order to avoid the problems caused by the bidirectional DC / DC converter, a Buck circuit and a Boost circuit are used to exchange power between the storage battery and the DC bus.

[0008] In view of these problems, scholars use new quasi-Z source high gain boost converter, has certain effect but this converter is more suitable for small power occasions, the interleaved Boost circuit solves the problem of large switch noise and current ripple of the traditional Boost circuit under large current, but the circuit is more complex, the control is more complicated. With the development of neural network and prediction algorithm, many scholars use neural network combined with prediction algorithm to push the control of Boost circuit to a new development. SUMMARY

[0009] The purpose of the present application is to solve the problems existing in the prior art, and a control method for a DC converter of a wind-solar dual storage microgrid is proposed. The dual storage battery is used to ensure the throughput of power. The power absorption circuit A and the power release circuit B are used to ensure that the bus voltage remains stable when the wind, light and load power fluctuate at the same time. In addition, the four-switch switching circuit is used to ensure that the dual storage battery is quickly and stably switched between the Buck and Boost circuits, i.e. the charging and discharging state.

[0010] In order to achieve the above purpose, the present application adopts the following technical scheme:

[0011] A control method for a DC converter of a wind-solar dual storage microgrid, comprising the following steps:

[0012] Step 1: The microgrid system includes a power generation system composed of two output modules of wind power and photovoltaic power generation, a dual storage battery system and a plurality of converters to form an energy regulation system. The wind power output voltage is controlled by an AC / DC rectifier to control the bus voltage; the dual storage battery system includes a power absorption circuit and a power release circuit and two groups of storage batteries; the DC converter A of the power absorption circuit works in Buck mode, and the DC converter B of the power release circuit works in Boost mode; by detecting the fluctuation of the DC bus voltage, the DC converter A and the DC converter B are triggered to work alternately; the DC converter A and the DC converter B work under the control of the outer voltage and the inner current double-loop control;

[0013] Step 2: The Boost converter uses sliding mode control to optimize the PI control of the voltage outer loop, stabilizes the output voltage and outputs the precision reference current I ref , using a linear quadratic regulator LQR instead of the current inner loop, outputting the switch PWM duty cycle required to suppress the bus voltage change, so that the output power of the storage battery reaches the ideal supply and demand compensation effect;

[0014] Step 2.1: The sliding mode control is based on voltage deviation and voltage deviation rate as variables to establish a sliding surface Where c is used to adjust the dynamic performance of the system. The c value can affect the response speed and stability of the system. The ultimate goal of the design is to make the voltage deviation zero and the voltage deviation change rate zero. The constant velocity reaching law is selected: Further optimize the system's adjustment time;

[0015] Step 2.2: Linear Quadratic Regulator LQR for Second-Order Linear Systems Design a linear feedback controller u = -Kx, where the control strategy is optimized based on the cost function This function is used to measure system performance. The control objective is to minimize the cost function J by selecting the values ​​of Q and R while ensuring system stability. The matrices Q and R are two diagonal matrices, respectively used to adjust the weights of the state vector x and input vector u during optimization. The state vector x represents the state space variables of the boost circuit, while the control input u represents the duty cycle D of the boost circuit.

[0016] Step 3: Under the condition of reasonable energy storage capacity configuration, use the ampere-hour integration method to predict and calculate the battery SOC. The basic principle of the ampere-hour integration method is expressed as follows: Where SOC0 represents the battery's initial state of charge, C represents the battery's total capacity, η represents the charge and discharge efficiency, and I represents the inductor current. After determining the battery SOC, the overcharge and overdischarge protection ranges are set. Based on these ranges, the four-switch charge and discharge switching circuit and dual energy storage battery logic are designed.

[0017] In step 1, the specific method includes the following: According to the permanent magnet synchronous generator power formula P = T m ×ω, we can see that the power of the permanent magnet synchronous generator is related to the torque and angular velocity. m =0.5ρπd 2 v 3 c p / n, speed Reference speed n ref It is the speed corresponding to the maximum torque of the fan, and n is controlled according to the optimal tip speed ratio. ref =30λv / πd, c p By the relationship: Calculated. In the formula, T m represents the torque of the permanent magnet synchronous generator, ρ is the gas density, d is the impeller diameter, v is the wind speed, c pis the wind energy utilization coefficient, n is the wind turbine speed, ω is the wind turbine angular velocity, d is the wind turbine diameter, β is the wind turbine pitch angle, and λ is the optimum tip speed ratio of the wind turbine. In the system, the wind turbine speed is controlled and the output voltage is achieved by the double closed-loop control of the wind turbine speed outer ring and the 0d-axis current inner ring. The speed difference Δn is obtained by subtracting the reference speed n ref The actual speed of the permanent magnet synchronous generator is subtracted from the reference speed to obtain the q-axis current reference value I sq * The q-axis current actual value I is obtained by subtracting the three-phase stator current output by the permanent magnet synchronous generator through coordinate transformation. sq The error of the q-axis current is obtained by subtracting the three-phase stator current output by the permanent magnet synchronous generator through coordinate transformation.

[0018] In step 2.1, the method specifically includes the following: calculating the voltage error e = U ref -U o Then the sliding mode surface The inductance current reference value I ref = I c + I l , I c is output by the ammeter, That is Thus the sliding mode control ends, and the stable output voltage and the current reference value are output to the LQR regulator in the rear stage to control the current.

[0019] In step 2.2, the method specifically includes the following: since the target of the linear quadratic regulator must be linear, the small signal model of the Boost circuit is first modeled, and the transfer function of the small signal model of the Boost circuit is written according to the established small signal model: According to the transfer function, the state space equation of the Boost circuit is obtained by the state space averaging method: According to the input-output relationship of the Boost circuit voltage The state space equation is rewritten Then the expression is obtained, u = 1-D. Another key of LQR is the selection of weight matrix Q and R. Q and R represent the importance of state vector x and control input u to the cost function J respectively. After selecting proper Q and R, gain matrix K is solved by Matlab function lqr(A, B, Q, R). The state space equation outputs to the observer to get the updated value of state at certain time. The observer is served by Kalman filter, which mainly consists of three steps: firstly, the prediction of state where is the prior state estimate (prediction) at time k, here A1is the transition state matrix, is the posterior state estimate (update) at time k-1, B1is the control input matrix, u k-1 is the control input vector. Then the prediction of error covariance, P k∣k-1 = A1P k-1∣k-1 A1 T + q, where P k∣k-1 is the prior error covariance matrix at time k, P k-1∣k-1 is the posterior error covariance matrix at time k-1, and q is the process noise covariance matrix. Finally, the update step, which combines the measurement to correct the predicted state and error covariance. Kalman gain K k = P k∣k-1 H T (HP k∣k-1 H T + R) -1 , where K k is the Kalman gain matrix at time k, H is the measurement matrix, R is the measurement noise covariance matrix, and finally the state update to get the posterior state estimate at time k where, is the posterior state estimate at time k, z k is the measurement at time k. After getting the state at time k, it is multiplied by the gain matrix K to get the control law u = -Kx. That is, u = -Kx = 1-D, then D = 1+Kx. The output duty cycle D is passed through a PWM generator to generate the corresponding PWM wave to control the power release circuit to output the power to suppress the bus voltage fluctuation;

[0020] In step 3, the following method is specifically adopted: firstly, the power absorption circuit (Buck circuit) or the power output circuit (Boost circuit) is determined according to the positive or negative of the difference ΔP between the total power output by the energy output end and the power consumed by the load end. When ΔP>0, it indicates that energy overflow occurs at this time, the power storage battery needs to absorb power, energy flows into the power storage battery from the bus, the Buck circuit starts to work, then the battery SOC obtained according to the ampere-hour integration method is used, the working interval of the battery is set to 20<SOC<80 to prevent overcharging and overdischarging, whether the SOC of the first battery is greater than 80 is judged, if not, the switch S1 is closed, and the first battery is charged; if yes, the switch S1 is disconnected, the switch S3 is closed, and the second battery is charged. When Δp<0, it indicates that energy shortage occurs at this time, the power storage battery needs to release power, energy flows into the bus from the power storage battery, the Boost circuit starts to work, whether the SOC of the first battery is less than 20 is judged, if not, the switch S4 is closed, and the first battery is discharged; if yes, the switch S4 is disconnected, the switch S2 is closed, and the second battery is discharged.

[0021] Compared with the prior art, the present application has the following beneficial effects:

[0022] 1、The present application makes the permanent magnet synchronous generator work at the maximum working point through the optimal tip speed ratio control, uses the outer rotating speed and the inner 0d axis current double closed loop control to make the fan output stable voltage when the wind speed is certain, then preliminarily stabilizes the bus voltage through the Buck circuit; the photovoltaic panel works at the maximum working point through the electric conductance increment method to obtain the maximum working efficiency of the photovoltaic panel.

[0023] 2、The present application uses the Boost circuit improved based on the sliding mode control and the LQR algorithm for the energy flow between the direct current bus and the power storage battery, so that when the power of the energy output end and the load power suddenly change, the power storage battery can quickly work and has good regulation time and overshoot.

[0024] 3、The present application uses double power storage batteries, a Buck circuit and a Boost circuit for the energy exchange between the direct current bus and the power storage battery, effectively avoids a series of problems caused by the insufficient capacity of a single battery and the use of a bidirectional DC / DC converter.

[0025] 4、The present application uses a four-switch switching circuit to quickly switch the double power storage batteries between the charging and discharging working conditions, and reduce the dead time and overshoot caused by the working condition switching. BRIEF DESCRIPTION OF DRAWINGS

[0026] Figure 1 The flow chart of the present application

[0027] Figure 2 The hardware structure schematic diagram of the wind and light double power storage battery in the present application

[0028] Figure 3 Results of the classic double-loop PI control, the double-loop control based on LQR improved inner loop, and the improved Boost circuit based on sliding mode control and LQR controller in the present application;

[0029] Figure 4 Results of the three methods for bus voltage stability when the system power fluctuates and switching is performed in the present application;

[0030] Figure 5 Schematic block diagram of the optimal tip speed ratio control of the fan system and the double-loop control of the outer rotational speed and the inner 0d-axis current in the present application. DETAILED DESCRIPTION

[0031] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings, so that the persons skilled in the art can better understand the advantages and features of the present application, and the protection scope of the present application can be defined more clearly. The described embodiments of the present application are only some of the embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by the persons skilled in the art without creative labor fall within the protection scope of the present application.

[0032] As shown in Figure 1 , a control method for a DC converter of a wind-solar dual-storage microgrid comprises the following steps:

[0033] 1) The power generation system comprises two output modules of wind power and photovoltaic power generation, and the wind power output voltage controls the bus voltage through an AC / DC rectifier. The photovoltaic panel works at the maximum power point by using the conductance increment method to find the maximum power point;

[0034] 1.1) The power generation system selects a permanent magnet synchronous generator as a fan. First, the optimal tip speed ratio control is used to obtain the maximum torque, then the double-loop control of the outer speed loop and the inner 0d-axis current loop is used to preliminarily stabilize the output voltage of the fan, and then the AC / DC converter is used to further stabilize the output voltage of the fan. According to the power formula p = T m × ω of the permanent magnet synchronous generator, the power of the permanent magnet synchronous generator is related to the torque T m and the angular velocity ω. 2 3 p The reference rotational speed n ref is the rotational speed corresponding to the maximum torque of the fan, which is calculated according to the optimal tip speed ratio control n ref = 30 λ v / π d, and c p is calculated by the relationship: ​​​

[0035] The calculation is obtained. In the system, through the fan speed outer ring, the 0d axis current inner ring double closed loop control to achieve the purpose of controlling the fan speed, stable voltage. Speed difference Δn is obtained by the difference between the reference speed n ref The speed difference Δn is obtained by the difference between the reference speed n sq * The q-axis current actual value I sq is obtained by the difference between the q-axis current reference value I m and the q-axis current actual value I p After PI regulator, the q-axis voltage is obtained, and similarly, the d-axis voltage can also be obtained. After obtaining the dq-axis voltage, coordinate transformation is performed again to transform the dq-axis voltage to αβ axis, and finally the space vector PWM (SVPWM) modulation is performed to obtain the PWM wave used to control the rectifier output stable DC voltage.

[0036] The letters involved in the above are as follows, T m represents the torque of the permanent magnet synchronous generator, ρ is the gas density, d is the impeller diameter, v is the wind speed, c p is the wind energy utilization coefficient, n is the fan speed, π is the angular velocity of the fan, d is the diameter of the fan, β is the pitch angle of the fan, and λ is the optimal tip speed ratio of the fan.

[0037] 1.2) Use the conductance increment method to find the maximum power point of the photovoltaic panel. The output voltage and output current of the photovoltaic panel are U pv , I pv . Take the derivative of both sides of P=UI with respect to U, From the power voltage curve, when (dP / dU)=0, it is at the maximum power point, that is, That is, Since the formula contains the denominator dU, consider the case of dU=0. When dU=0, if dI=0, then the system is at the maximum power point at this time, if dI>0, then this moment is on the left side of the maximum power point, and vice versa. When dU≠0, compare and , that is, the size of the negative number of conductance g. If this moment is on the left side of the maximum power point, and vice versa;

[0038] 2) Double energy storage battery system includes power absorption circuit and power release circuit. DC converter A of power absorption circuit works in Buck mode, DC converter B of power release circuit works in Boost mode. By detecting the fluctuation of DC bus voltage, trigger two DC converters A, B to work alternately. Converter A, B works in outer voltage and inner current double loop control. Boost converter uses sliding mode control to optimize the PI control of voltage outer loop, so that the value of output reference current I ref is as accurate as possible. Use LQR algorithm instead of traditional current inner loop, output duty cycle following power demand changes, so that the output power of energy storage battery reaches the optimal control effect;

[0039] 2.1) The sliding mode control system is based on voltage deviation and voltage deviation rate as variables, and the sliding surface is established The final goal is to make the voltage deviation 0 and the voltage deviation rate 0. In the step, according to the selection of sliding mode control reaching law, among the common three kinds of reaching law: the constant speed reaching law is like The exponential reaching law is like k>0 and the power reaching law The constant speed reaching law with the shortest adjustment time is selected as the reaching law of this time sliding mode control. The voltage error e = U ref -U o , then the sliding surface The inductance current reference value I ref = I c + I l , I c is output by ammeter, That is Thus the sliding mode control ends, and the output current reference value I ref is sent to the LQR regulator in the rear stage to control the current.

[0040] 2.2) Linear quadratic regulator (LQR) designs a linear feedback controller u = -Kx for a second-order linear system The optimization of control strategy is based on the cost function The function is used to measure the pros and cons of system performance. The control target is to minimize the cost function J by choosing the value of Q and R reasonably under the premise of meeting the system stability. Matrix Q and R are two diagonal matrices, which are used to adjust the weight of state vector x and input vector u in optimization. In the system studied in this paper, the state vector x is the state space variable of the Boost circuit, and the control input u represents the duty cycle D of the Boost circuit. Since the target of the linear quadratic regulator is linear, the small signal model of the Boost circuit is first established, and the transfer function of the small signal model of the Boost circuit is written according to the established small signal model: According to the transfer function, the state space equation of the Boost circuit obtained by the state space averaging method is: According to the input-output relationship of the voltage of the Boost circuit Rewrite the state space equation Point Then the expression In u = 1-D. Another key of the linear quadratic regulator is the selection of the weight matrix Q and R. Q and R represent the importance of the state vector x and the control input u to the cost function J. After selecting appropriate Q and R, the gain matrix K is solved by the Matlab function lqr(A, B, Q, R). The state space equation is output to the observer to get the updated value of the state at a certain time. The observer is played by the Kalman filter, which mainly consists of three steps: first, the prediction of the state Where is the prior state estimation (prediction value) at time k, here A1 is the transition state matrix, is the posterior state estimation (updated value) at time k-1, B1 is the control input matrix, u k-1 is the control input vector. Then the error covariance is predicted, P k∣k-1 = A1P k-1∣k-1 A1 T + q, where P k∣k-1 is the prior error covariance matrix at time k, P k-1∣k-1 is the posterior error covariance matrix at time k-1, and q is the process noise covariance matrix. Finally, the update step is used to correct the predicted state and error covariance by combining the measurement value. The Kalman gain K k = P k∣k-1 H T (HP k∣k-1 H T + R) -1 , where K kis the Kalman gain matrix at time k, H is the measurement matrix, R is the measurement noise covariance matrix, and finally the state update is performed to obtain the state at time k wherein, is the posterior state estimation at time k, z k is the measurement value at time k, after obtaining the state at time k, the gain matrix K is multiplied to obtain the control law u = -Kx, that is, u = -Kx = 1-D, then D = 1+Kx. The duty cycle D of the output is passed through a PWM generator to generate a corresponding PWM wave to control the power release circuit to output power to suppress bus voltage fluctuations;

[0041] 3) In the reasonable energy storage capacity configuration condition, the ampere-hour integral method is used to predict and calculate the battery SOC, and the basic principle of the ampere-hour integral method is expressed by a formula Wherein, SOC0 represents the initial state of charge of the battery, C represents the total capacity of the battery, η is the charging and discharging efficiency, I is the inductance current, and in the reasonable energy storage capacity configuration condition, η = 100%. After obtaining the battery SOC, the battery overcharge and overdischarge protection interval is set, and the four-switch charging and discharging switching circuit and the double energy storage battery logic are designed according to the interval. First, according to the positive and negative of the difference ΔP between the total power output at the energy output end and the power consumed at the load end, it is determined whether the power absorption circuit (Buck circuit) or the power output circuit (Boost circuit) is used. When ΔP>0, it indicates that the energy is overflowing at this time, and the power storage battery needs to absorb power, and the Buck circuit starts to work. Then, according to the battery SOC obtained by the ampere-hour integral method, the working interval of the battery is set to 20<SOC<80 to prevent overcharging and overdischarging. It is judged whether the SOC of the first battery is greater than 80, if not, the switch S1 is closed, and the first battery is charged; if yes, the switch S1 is opened, and the switch S3 is closed, and the second battery is charged. When ΔP<0, it indicates that the energy is insufficient at this time, and the power storage battery needs to release power, and the Boost circuit starts to work. It is judged whether the SOC of the first battery is less than 20, if not, the switch S4 is closed, and the first battery is discharged; if yes, the switch S4 is opened, and the switch S2 is closed, and the second battery is discharged.

[0042] Figure 2 The effect of the Boost circuit in Figure 3 is shown in The present application is to realize the bus voltage stability of the wind-solar double energy storage battery when the state switching or the power appears large fluctuation, and finally realize the stability of the power.

[0043] Figure 3 The analysis is carried out, and the judgment of the Boost circuit boosting effect mainly has three standards: the regulation time t r , the overshoot B and the bus voltage ripple ΔU. The input voltage V Figure 3 in the Boost simulation parameter setting is 800Vin = 300V, L = 0.00026H, C = 0.0002F, R = 20Ω, switch frequency f = 20kHz, the outer loop PI parameter of double loop PI after parameter tuning is k p = 0.6, k i = 30, the inner loop PI parameter is k p = 0.6, k i = 10. The outer loop PI parameter of double loop PI is k Figure 3 It can be seen that the classic voltage outer loop current inner loop double loop PI control has a good overshoot, but its regulation time reaches t r = 0.1s, voltage ripple ΔU = 1.25%, due to the disadvantages of double loop control, the regulation effect of current inner loop is relatively poor, therefore, the LQR regulator is used to improve the current inner loop, so that the final control is more accurate. The specific parameter setting of LQR regulator is as follows: matrix C = [1 0], D = 1, According to the algorithm lqr(A, B, Q, R) of Matlab, the feedback gain matrix K = [3.0967 3.1589] is calculated. According to the real-time state x observed by Kalman filter, the real-time control input u = -Kx is obtained. The controller has obvious advantages on voltage ripple, and the voltage ripple ΔU is controlled to 0.2%, but there is a large overshoot, and the regulation time is not improved. Therefore, the voltage outer loop is optimized by using sliding mode control, so that the whole controller has great improvement in reducing overshoot, shortening regulation time and suppressing voltage ripple, and the specific performance is t r = 0.01s, ΔU = 0.2%, B = 1.25, compared with the above two methods, the controller proposed in the application has obviously better effect.

[0044] The controller is used in a wind-solar dual energy storage system and simulated in simulink. Basic settings of the wind-solar dual energy storage system are as follows: the wind speed of the fan is 5 m / s, the wind speed is cut out at 12 m / s, the voltage fluctuation range without voltage reduction is 850-1500V, the output power range is 50-300KW. The photovoltaic panel uses a photovoltaic array of 15 columns and 10 rows, each photovoltaic panel reaches the maximum power point at 25 DEG C and a light intensity of 1000Lx, the maximum output power of a single photovoltaic panel is 600W, the open circuit voltage at the maximum power point is 40V, and the short circuit current is 15A. The present application aims to stabilize the DC bus voltage at 800V, and when the wind speed or light intensity changes, the load demand power changes, and the bus voltage can still be stabilized. The LQR double closed-loop controller based on the improved sliding mode control has a significantly shorter adjustment time when the fan is reduced once. The slope function is used to control the slow decline of the wind speed and light intensity, and the pure resistance load resistance is slowly reduced to simulate the situation of weak wind and light at night and the increase of power demand. At 1.8s, the power provided by the energy output end is insufficient to maintain the power consumed by the load, the bus voltage starts to drop, and the dual energy storage system starts to work to provide power to maintain the stability of the bus voltage. The classic double closed-loop PI controller has a short adjustment time, but the adjustment time of the whole system is long, and the voltage ripple after adjustment is large, ΔU=1.25%, the double-loop control using the LQR improved current inner loop has obvious improvement on the bus voltage ripple, ΔU=0.2%, but at the same time, the overshoot B o =30. The LQR double closed-loop controller based on the improved sliding mode control has an adjustment time t r =0.095s, and the voltage ripple ΔU=0.2%, and the overshoot B o =10, which shows that the controller has good sensitivity and robustness.

[0045] In summary, the Boost circuit based on the sliding mode control and the LQR algorithm is used for the energy flow between the DC bus and the energy storage battery, so that when the energy output end power and the load power change suddenly, the energy storage battery can quickly respond and work, and has good robustness and rapidity; the double energy storage battery is used, a Buck and a Boost circuit are used for energy exchange between the DC bus and the energy storage battery, a series of problems caused by insufficient capacity of a single battery and use of a bidirectional DC / DC converter are avoided, and when the grid power fluctuates, the adjustment time is fast and the overshoot is small; the four-switch switching circuit is used to ensure that the double energy storage battery quickly switches between charging and discharging conditions, and reduce the dead time and overshoot caused by the switching of the working conditions.

[0046] The description and practice of the present application are easy to think and understand for the ordinary skilled in the art, and several improvements and refinements can be made without departing from the principles of the present application. Therefore, the modifications or improvements made without departing from the spirit of the present application should be considered as the protection scope of the present application.

Claims

1. A control method for a DC converter in a wind-solar dual-storage microgrid, characterized in that: It includes the following steps: Step 1: The microgrid system includes a power generation system composed of two output modules of wind power generation and photovoltaic power generation, and an energy regulation system composed of a dual energy storage battery system and multiple converters. The output voltage of the wind power is used to control the bus voltage through an AC / DC rectifier; the dual energy storage battery system includes a power absorption circuit, a power release circuit and two groups of energy storage batteries; the DC converter A of the power absorption circuit operates in the Buck mode, and the DC converter B of the power release circuit operates in the Boost mode; by detecting the fluctuation of the DC bus voltage, the DC converter A and the DC converter B are triggered to work alternately, and both the DC converter A and the DC converter B operate under the double closed-loop control of external voltage and internal current; Step 2: The Boost converter uses sliding mode control to optimize the PI control of the voltage outer loop, stabilize the output voltage, and output a high-precision reference current I ref , a linear quadratic regulator LQR is used to replace the current inner loop, outputting the switch PWM duty cycle required to smooth the bus voltage change, so that the output power of the energy storage battery can achieve the ideal supply and demand compensation effect; Step 2.1: Sliding mode control uses voltage deviation and voltage deviation change rate as variables to establish a sliding mode surface. Where c is used to adjust the dynamic performance of the system. The c value can affect the response speed and stability of the system. The ultimate goal of the design is to make the voltage deviation zero and the voltage deviation change rate zero. The constant velocity reaching law is selected: Further optimize the system's adjustment time; Step 2.2: Linear Quadratic Regulator LQR for Second-Order Linear Systems Design a linear feedback controller u = -Kx, where the control strategy is optimized based on the cost function This function is used to measure the performance of the system. The control objective is to minimize the cost function J by selecting the values ​​of Q and R while ensuring system stability. The matrices Q and R are two diagonal matrices used to adjust the weights of the state vector x and input vector u in the optimization process, respectively. The state vector x is the state space variable of the boost circuit, while the control input u represents the duty cycle D of the boost circuit. Step 3: Under the condition of reasonable energy storage capacity configuration, use the ampere-hour integration method to predict and calculate the battery SOC. The basic principle of the ampere-hour integration method is expressed as follows: Where SOC0 represents the battery's initial state of charge, C represents the battery's total capacity, η represents the charge and discharge efficiency, and I represents the inductor current. After obtaining the battery SOC, the battery overcharge and overdischarge protection interval is set, and the four-switch charge and discharge switching circuit and dual energy storage battery logic design are based on this interval.

2. The control method for a DC converter for a wind-solar dual-storage microgrid according to claim 1, characterized in that: In step 1, the method specifically includes the following: According to the permanent magnet synchronous generator power formula P=T m ×ω, it can be seen that the power of the permanent magnet synchronous generator is related to the torque and angular velocity; the torque T m =0.5ρπd 2 v 3 c p / n, angular velocity Reference speed n ref It is the speed corresponding to the maximum torque of the fan, and n is controlled according to the optimal tip speed ratio. ref =30λv / πd, c p By the relationship: Calculated, where T m represents the torque of the permanent magnet synchronous generator, ρ is the gas density, d is the impeller diameter, v is the wind speed, c p is the wind energy utilization coefficient, n is the wind turbine speed, ω is the wind turbine angular velocity, β is the wind turbine pitch angle, and λ is the optimal tip speed ratio of the wind turbine. The wind turbine speed and output voltage are controlled by the double closed-loop control of the wind turbine speed outer loop and the 0d axis current inner loop. The speed difference Δn is determined by the reference speed n ref The actual speed of the permanent magnet synchronous generator is obtained by subtracting it from the actual speed, and the q-axis current reference value I is obtained after passing through the PI regulator. sq * , and the actual value of the q-axis current I obtained by the coordinate change of the three-phase stator current output by the permanent magnet synchronous generator sq The error of the q-axis current is obtained by difference, and the q-axis voltage is obtained through the PI regulator. Similarly, the d-axis voltage can also be obtained. After obtaining the dq-axis voltage, the coordinates are changed again to transform the dq-axis voltage to the αβ axis. Finally, the PWM wave is obtained through space vector PWM modulation, which is used to control the rectifier to output a stable DC voltage.

3. The control method for a DC converter for a wind-solar-storage dual-grid according to claim 1, characterized in that: In step 2.1, the following method is specifically included: Calculate the voltage error e=U ref -U o , then the sliding surface Inductor current reference value I ref =I c +I l , where I c Output from the ammeter, Right now At this point, the sliding mode control ends, the output voltage is stabilized and the output current reference value I is output. ref To the subsequent LQR regulator, the current is controlled.

4. The control method for a DC converter for a wind-solar-storage dual-grid according to claim 1, characterized in that: In step 2.2, the specific method includes the following: Since the target of the linear quadratic regulator must be linear, the small signal model of the boost circuit is firstly constructed, and the transfer function of the small signal model of the boost circuit is written based on the established small signal model: According to the transfer function, the state space equation of the Boost circuit is obtained by the state space averaging method: According to the input and output relationship of the Boost circuit voltage Rewrite the state space equations Regular Expression middle, u=1-D; Another key to the linear quadratic regulator is the selection of weight matrices Q and R, which represent the importance of the state vector x and the control input u to the cost function J, respectively. After selecting appropriate Q and R, the gain matrix K is solved by the Matlab function lqr(A, B, Q, R), and the state space equation is output to the observer to obtain the updated value of the state at a certain moment. The observer is played by the Kalman filter, which is divided into three steps: the first is the prediction of the state in is the prior state estimate at time k, where A1 is the transfer state matrix, is the posterior state estimate at time k-1, B1 is the control input matrix, u k-1 is the control input vector; followed by the prediction of the error covariance, P k∣k-1 =A1P k-1∣k-1 A1 T +q, where P k∣k-1 is the prior error covariance matrix at time k, P k-1∣k-1 is the posterior error covariance matrix at time k-1, and q is the process noise covariance matrix; Finally, there is the update step, which combines the measured values ​​to correct the predicted state and error covariance; the Kalman gain K k =P k∣k-1 H T (HP k∣k-1 H T +R) -1 , where K k is the Kalman gain matrix at time k, H is the measurement matrix, R is the measurement noise covariance matrix, and finally the state is updated to obtain the state at time k. in, is the posterior state estimate at time k, z k It is the measured value at time k. After obtaining the state at time k, it is multiplied by the gain matrix K to obtain the control law u=-Kx, that is, u=-Kx=1-D, then D=1+Kx. The output duty cycle D is passed through a PWM generator to generate the corresponding PWM wave to control the power release circuit to output power to smooth the bus voltage fluctuation.

5. The control method for a DC converter for a wind-solar-storage dual-grid according to claim 1, characterized in that: In Step 3, the following method is specifically adopted: First, select whether to use the power absorption circuit or the power output circuit according to the positive or negative of the difference ΔP between the total power output from the energy output end and the power consumed by the load end; when ΔP>0, it means that energy overflows at this time, and the energy storage battery needs to absorb power, and the Buck circuit starts to work, and the energy flows from the bus into the energy storage battery; then, according to the battery SOC obtained by the ampere-hour integration method, to prevent overcharging and over-discharging, the working range of the battery is set to 20<SOC<80, and it is judged whether the SOC of the first battery is greater than 80. If not, the switch S1 is closed and the first battery is charged; if so, the switch S1 is disconnected and S3 is closed, and the second battery is charged; when ΔP<0, it means that energy is insufficient at this time, and the energy storage battery needs to release power, and the energy flows from the energy storage battery into the bus, and the Boost circuit starts to work. It is judged whether the SOC of the first battery is less than 20. If not, the switch S4 is closed and the first battery discharges; if so, the switch S4 is disconnected and S2 is closed, and the second battery discharges.

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