Micro-grid oscillation suppression control method and system based on adaptive static-dynamic model

Abstract

The invention discloses a micro-grid oscillation suppression control method and system based on a self-adaptive static-dynamic model. The method comprises the following steps: predicting a direct-current side capacitor voltage value, an alternating-current side three-phase capacitor voltage value and an alternating-current side three-phase inductance current value at a next moment according to a value acquired at a current moment and obtained by sampling; taking the direct current side capacitor voltage value, the alternating current side three-phase capacitor voltage value and the alternating current side three-phase inductance current value obtained through prediction as well as the deviation of the expected values as control targets, and establishing a control target function in combination with each control target weight obtained through calculation according to an adaptive weight function; and modulating a voltage vector output by the control objective function by adopting a zero voltage vector injection modulation method to realize fixed frequency control. According to the application, a direct current side control target is added on the basis of model prediction control, an adaptive target function is adopted, the target function is evaluated to obtain an optimal voltage vector, and then a corresponding switching tube state is obtained by applying space vector pulse width modulation.

Description

Technical Field

[0001] The present application relates to the field of microgrid control technology, and in particular to a microgrid oscillation suppression control method and system based on an adaptive static-dynamic model. Background Art

[0002] In recent years, with the rise of the concept of "energy transformation and green development", microgrids composed of distributed power generation equipment and power consumption equipment have come into being. They have the advantages of simple structure, high efficiency and strong reliability. They are widely used in modern grid-connected autonomous distribution systems such as electric vehicles, high-speed railways, green buildings, future carrier-based aircraft power systems, and data centers.

[0003] The end users of DC microgrids are mainly electronic loads. When these electronic loads are strictly regulated, negative impedance effects may occur, which manifest as constant power loads (CPLs), which have a certain impact on the stability of the system. At the same time, the interaction between multiple converters in the microgrid can also cause power oscillations and even make the system unstable.

[0004] In order to overcome this instability, people have studied stabilization strategies in recent years. The traditional method is the passive damping method, which increases the system damping by connecting additional RC or RL filters. Its advantage is that the method is simple, but it also increases the cost and volume of the system. Another method is to add various control technologies to the load or converter, which is called active damping method. This method is more complex but less expensive. Active damping methods are divided into linear and nonlinear methods. The linear method uses a linear feedback closed-loop control transfer function, which is easier to stabilize small signals; the nonlinear method has robustness and faster dynamic performance in a large range, and is mainly suitable for large signal models. With the increasing popularity of nonlinear controlled converters, the method of using nonlinear control to stabilize microgrids has received more and more attention. Among the nonlinear methods, Model Predictive Control (MPC) has an intuitive concept and can achieve fast tracking response. It is widely used in applications such as three-phase rectifiers, three-phase inverters, and permanent magnet synchronous motors.

[0005] Finite Control Set Model Predictive Control (FCS-MPC) is an important branch of MPC and the most widely used MPC method. However, traditional FCS-MPC has the problems of difficult weight factor design and unstable switching frequency. The selection of traditional FCS-MPC weight factors mainly relies on experience to select fixed weight factors, which requires a lot of attempts, and the fixed weight factors make the system's dynamic adaptability weak. In power electronic systems, changing switching frequencies can lead to a wide range of harmonic distribution, seriously affecting the power quality and even causing resonant instability in the system. Summary of the invention

[0006] In order to solve the problems of difficult weight factor design and non-fixed switching frequency in traditional FCS-MPC, this application proposes a microgrid oscillation suppression control method and system based on an adaptive static-dynamic model. This application adds a DC side control target on the basis of model predictive control, and adopts an adaptive objective function to evaluate the objective function to obtain the optimal voltage vector, and then uses space vector pulse width modulation to obtain the corresponding switch tube state.

[0007] This application is implemented through the following technical solutions:

[0008] A microgrid oscillation suppression control method based on an adaptive static-dynamic model, the microgrid oscillation suppression control method comprising:

[0009] Using the pre-built prediction model, based on the sampled DC side capacitor voltage value, DC side inductor current value, AC side three-phase capacitor voltage value, AC side three-phase inductor current value and AC side three-phase output current value at the current moment, the DC side capacitor voltage value, AC side three-phase capacitor voltage value and AC side three-phase inductor current value at the next moment are predicted;

[0010] The predicted DC side capacitor voltage value, AC side three-phase capacitor voltage value, AC side three-phase inductor current value and their expected value deviation are used as control targets, and the control target function is established by combining the weights of each control target calculated according to the adaptive weight function;

[0011] A modulation method of zero voltage vector injection is adopted to modulate the voltage vector output by the control objective function to realize constant frequency control.

[0012] In some embodiments, the prediction model building process specifically includes:

[0013] The mathematical model of the DC side LC filter is established and expressed as:

[0014]

[0015] Among them, L dc , C dc are the DC side inductance and DC side capacitance respectively; v s 、v dc 、i pol 、i dc They are the DC side input voltage value, DC side capacitor voltage value, inverter input current value and DC side inductor current value respectively;

[0016] The discrete time model of the DC side is:

[0017]

[0018] Among them, i pol_i and i pol_f are the inverter input current at time k and the inverter input current at time k+1, T s is the sampling period, v dc (k+1) and v dc (k) represents the DC link capacitor voltage value at the next moment and the DC link capacitor voltage value at the current moment respectively.

[0019] In some embodiments, the prediction model building process further includes:

[0020] The mathematical model of the AC side LC filter is established and expressed as:

[0021]

[0022] Among them, L and C are the inductance and capacitance of the AC side respectively, v i,αβ 、v C,αβ 、i L,αβ and i o,αβ They are the three-phase output voltage, three-phase capacitor voltage, three-phase inductor current value and three-phase output current value of the inverter in the α-β two-phase coordinate system respectively;

[0023] Through the zero-order hold discretization method, the discrete time model of the AC side is obtained as follows:

[0024]

[0025] in,

[0026]

[0027] Among them, i L,αβ (k+1),i L,αβ (k) represents the three-phase inductor current value of the AC side at the next moment and the three-phase inductor current value of the AC side at the current moment respectively; v C,αβ (k+1),v C,αβ(k) respectively represent the three-phase capacitor voltage value on the AC side at the next moment and the three-phase capacitor voltage value on the AC side at the current moment.

[0028] In some implementations, the established control objective function is expressed as:

[0029] G=λ dc G dc +λ v G v +λ i G i

[0030] in,

[0031]

[0032] Among them, λ dc , i and λ v are the weight factors of each control target item, C represents the capacitance value on the AC side, and w ref represents the reference angular frequency, They represent the reference values ​​of the DC side capacitor voltage, the α component of the AC side capacitor voltage, and the β component of the AC side capacitor voltage, respectively. Cα 、v Cβ Respectively represent the α and β components of the AC side capacitor voltage, i Cα 、i Cβ They represent the α and β components of the AC side inductor current respectively.

[0033] In some embodiments, the adaptive weight function includes:

[0034] The adaptive weight function of the DC side capacitor voltage is:

[0035]

[0036] The adaptive weight function of the AC side capacitor voltage is:

[0037]

[0038] The adaptive weight function of the AC side inductor current is:

[0039]

[0040] in,

[0041]

[0042] v allow-dc 、v allow-ac 、i allow-acThey represent the allowable voltage error on the DC side, the allowable voltage error on the AC side, and the allowable current error on the AC side respectively.

[0043] In some implementations, the modulation method of zero voltage vector injection specifically includes:

[0044] Reduce the original eight voltage vectors:

[0045] V i * =V i ×m

[0046] Among them, V i is the i+1th voltage vector, i=0,2,…7; m is the voltage vector reduction coefficient;

[0047] A zero voltage vector of a fixed duration is inserted in each modulation cycle, so that the action time of the zero voltage vector is increased.

[0048] In a second aspect, the present application proposes a microgrid oscillation suppression control system based on an adaptive static-dynamic model, wherein the microgrid oscillation suppression control system comprises:

[0049] A prediction module, wherein the prediction module uses a pre-built prediction model to predict the DC capacitor voltage value, the AC side three-phase capacitor voltage value, and the AC side three-phase inductor current value at the next moment based on the sampled DC side capacitor voltage value, the DC side inductor current value, the AC side three-phase capacitor voltage value, the AC side three-phase inductor current value, and the AC side three-phase output current value at the current moment;

[0050] An adaptive weight calculation module, wherein the adaptive weight calculation module is used to calculate a control target weight according to an adaptive weight function;

[0051] And, an objective function evaluation module, which uses the predicted DC side capacitor voltage value, AC side three-phase capacitor voltage value and AC side three-phase inductor current value and their expected value deviations as control targets, combines the weights of each control target, and establishes a control objective function.

[0052] In some embodiments, the microgrid oscillation suppression control system further includes:

[0053] The vector control module adopts a modulation method of zero voltage vector injection to modulate the voltage vector output by the control objective function to achieve fixed frequency control.

[0054] In a third aspect, the present application proposes a computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the above method when executing the computer program.

[0055] In a fourth aspect, the present application proposes a computer-readable storage medium having a computer program stored thereon, wherein the computer program implements the steps of the above method when executed by a processor.

[0056] The present application proposes a microgrid oscillation suppression control method and system based on an adaptive static-dynamic model. On the basis of traditional model predictive control, a DC side control target is added, and a static-dynamic adaptive objective function is designed, which eliminates the selection process of fixed weight factors and improves the adaptive ability of the system. In the case of large oscillations, the DC microgrid can be stabilized in a short time and the AC side can maintain good voltage quality, thereby improving the stability and dynamic performance of the system. A modulation method of zero voltage vector injection is also proposed to realize fixed frequency control. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] The drawings described herein are used to provide a further understanding of the embodiments of the present application, constitute a part of the present application, and do not constitute a limitation on the embodiments of the present application. In the drawings:

[0058] Figure 1 A flow chart of the method proposed in the embodiment of the present application;

[0059] Figure 2 is the inverter output voltage vector;

[0060] Figure 3 is the voltage vector action time relationship;

[0061] Figure 4 It is the SVPWM adjustment process;

[0062] Figure 5 A block diagram of the system principle proposed in the embodiment of the present application;

[0063] Figure 6 is the integral of the number of periodic switches; where (a) is the integral curve of the number of switches after fixed frequency processing; (b) is the integral curve of the number of switches under traditional MPC control;

[0064] Figure 7 Comparison of steady-state performance and dynamic performance; (a) is the output waveform of the AC side and the output waveform of the DC side when the fixed-frequency stabilization control method (fixed weight factor) is adopted; (b) is the output waveform of the AC side and the output waveform of the DC side under traditional MPC control;

[0065] Figure 8 FFT analysis comparison; (a) is the FFT analysis diagram of the output three-phase AC voltage when the fixed-frequency stabilization control method (fixed weight factor) is adopted; (b) is the FFT analysis diagram of the output three-phase AC voltage under traditional MPC control;

[0066] Fig. 9 Performance comparison for different DC weight factors; (a) is the DC side voltage waveform and the AC side capacitor voltage waveform when the DC weight factor is 0; (b) is the DC side voltage waveform and the AC side capacitor voltage waveform when the DC weight factor is 0.3; (c) is the DC side voltage waveform and the AC side capacitor voltage waveform when the DC weight factor is 1; (d) is the DC side voltage waveform and the AC side capacitor voltage waveform when the DC weight factor is 5;

[0067] Fig.10 Changes in the proportion of exchanges;

[0068] Fig.11 For the comparison of steady-state performance and dynamic performance; wherein (a) is the AC side output waveform and the DC side output waveform diagram when the fixed-frequency stabilization control method (adaptive weight function) proposed in this embodiment is adopted; (b) is the AC side output waveform and the DC side output waveform diagram when the fixed-frequency stabilization control method (fixed weight factor) is adopted;

[0069] Fig.12 FFT analysis and comparison; wherein, (a) is the FFT analysis diagram of the AC side capacitor voltage before the load jump when the fixed-frequency stabilization control method (adaptive weight function) proposed in this embodiment is adopted; (b) is the FFT analysis diagram of the AC side capacitor voltage after the load jump when the fixed-frequency stabilization control method (adaptive weight function) proposed in this embodiment is adopted; (c) is the FFT analysis diagram of the AC side capacitor voltage before the load jump when the fixed-frequency stabilization control method (fixed weight factor) proposed in this embodiment is adopted; (b) is the FFT analysis diagram of the AC side capacitor voltage after the load jump when the fixed-frequency stabilization control method (fixed weight factor) proposed in this embodiment is adopted. DETAILED DESCRIPTION

[0070] In order to make the objectives, technical solutions and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with examples and drawings. The illustrative implementation scheme of the present application and its description are only used to explain the present application and are not intended to limit the present application.

[0071] Embodiment 1:

[0072] The traditional FCS-MPC method has the following problems: (1) The switching frequency is not fixed, and it is difficult to design a filter to filter out high-frequency harmonics according to the switching frequency; (2) The DC side oscillation problem is not considered. When a large oscillation occurs on the DC side, it will affect the voltage quality on the AC side; (3) The weight factor is a fixed value, the design process is complicated, the system does not have the ability to adjust itself, and the anti-interference ability is not strong. In view of this, this embodiment proposes a microgrid oscillation suppression control method based on an adaptive static-dynamic model. This embodiment first proposes a fixed-frequency processing method for zero voltage vector injection, and then adds a DC side control target on the basis of model predictive control, designs an adaptive objective function, evaluates the objective function to obtain the optimal voltage vector, and finally uses space vector pulse width modulation to obtain the corresponding switch state.

[0073] like Figure 1 As shown, the method proposed in this embodiment includes the following steps:

[0074] Step 100, using a pre-built prediction model, based on the sampled DC side capacitor voltage value, DC side inductor current value, AC side three-phase capacitor voltage value, AC side three-phase inductor current value and AC side three-phase output current value at the current moment, predict the DC side capacitor voltage value, AC side three-phase capacitor voltage value and AC side three-phase inductor current value at the next moment.

[0075] Step 200, using the predicted DC side capacitor voltage value, AC side three-phase capacitor voltage value and AC side three-phase inductor current value and their expected value deviation as the control target, and combining the weights of each control target calculated according to the adaptive weight function to establish a control target function.

[0076] Step 300, adopting a modulation method of zero voltage vector injection to modulate the voltage vector output by the control objective function to achieve constant frequency control.

[0077] Furthermore, the traditional model predictive control is based on eight voltage vectors (such as Figure 2 After the optimal voltage vector is determined, it will continue to act throughout the control cycle, which is equivalent to the full duty cycle state in PWM modulation technology. Therefore, when the traditional model prediction method is used, each switch tube has only two states: zero duty cycle and full duty cycle in one control cycle. For example, in the process of changing from [0 01] to [1 1 0], the three bridge arms all have switching actions (defined as S a , S b , S c ), and in the process of changing from [0 0 1] to [1 0 1], only one bridge arm has switching action, which leads to the problem of unstable frequency. In the traditional model predictive control technology, the relationship between the switching state and the output voltage vector is shown in Table 1.

[0078] Table 1 Relationship between switch state and output voltage vector

[0079]

[0080]

[0081] Different from the traditional model prediction, SVPWM modulation includes sector judgment, vector action time calculation, seven-segment processing and modulation wave generation, and inserts two zero vector switching states [0 0 0] and [1 1 1] in the control cycle, so that each bridge arm is switched only once in one control cycle. Therefore, this embodiment adopts the SVPWM modulation method to modulate the voltage vector, which can realize fixed frequency control.

[0082] In order to add a zero vector within a control cycle, the original eight voltage vectors are reduced:

[0083] V i * =V i ×m (1)

[0084] Among them, V i is the i+1th voltage vector, i=0,2,…7; m is the voltage vector reduction coefficient. Reducing the voltage vector is equivalent to inserting a zero vector of a fixed time in each modulation cycle, which increases the action time of the zero voltage vector. Since the voltage change rate generated by the zero voltage vector is small and the voltage change rate generated by the non-zero vector is large, the increase in the zero voltage vector action time will lead to a decrease in the output voltage ripple and an increase in the steady-state error. In order to reduce the steady-state error, the value of m should be selected to be close to 1.

[0085] like Figure 3 As shown in Table 1, after the voltage vector in Table 1 is reduced, when the optimal vector is a non-zero vector, V i (i=1,2,…6), V0 and V7 all act; when the optimal vector is zero vector, V0 and V7 act. Therefore, the evaluation switch state also changes.

[0086] Let S a * , S b * , S c * To evaluate the equivalent switching state after the voltage vector is reduced, its size is related to the conduction time of the three bridge arms, and S a * For example, when the upper tube opening time is T S When S a* =1; the lower tube opening time is T S When S a * =0; in order to achieve fixed frequency processing, the evaluation voltage vector is reduced, and a zero voltage vector is inserted in the modulation period. Since m is slightly less than 1, the action time of V7 can be ignored (except when the optimal vector is a zero vector); therefore, the conduction time of each bridge arm is:

[0087] [T ai T bi T ci ]=m[S a S b S c ]T s (2)

[0088] Among them, T ai , T bi , T ci The optimal vectors are V i The conduction time of the three bridge arm upper tubes, T S is the sampling period; note that when the optimal vector is the zero vector, V0 and V7 act on T S / 2, so we have:

[0089]

[0090] According to equations (2) and (3), after the evaluation voltage vector is reduced, the relationship between its equivalent switch state and the output voltage vector is shown in Table 2.

[0091] Table 2 Relationship between equivalent switch state and output voltage vector

[0092]

[0093] According to the voltage vector action time relationship, the SVPWM modulation process (taking the modulation process of V1 as an example) is as follows: Figure 4 As shown in the figure. In a control cycle, each switch tube has three possible actions: keeping the original state unchanged, turning on, and turning off. This leads to the non-fixed switching frequency of the traditional model predictive control. Figure 4 It can be seen that the fixed frequency processing method adopted in this embodiment inserts a zero vector in each modulation cycle, and each switch tube is turned on and off once in a modulation cycle, so its switching frequency is determined by the frequency of the modulation wave, thereby realizing fixed frequency processing.

[0094] Furthermore, the prediction model building process specifically includes the following steps:

[0095] First, the mathematical model of the DC side LC filter is established. The differential equation of the DC side LC filter is:

[0096]

[0097] Among them, L dc , C dc are the DC side inductance and DC side capacitance respectively. s 、v dc 、i pol 、i dc They are the DC side input voltage value, DC side capacitor voltage value, inverter input current value and DC side inductor current value respectively.

[0098] Among them, the formula for the inverter input current is:

[0099]

[0100] Where T is the Clark equal-amplitude transformation matrix, S a * , S b * , S c * To evaluate the equivalent switching state after the switching vector is reduced, i Lα is the α component of the three-phase inductor current value, i Lβ is the β component of the three-phase inductor current. For the DC side, when the DC side inductance value is relatively large, the DC side current can be regarded as a constant, so the discrete time model of the DC side is:

[0101]

[0102] Among them, i pol_i and i pol_f are the inverter input current at time k and the inverter input current at time k+1, T s is the sampling period. Due to the existence of large inductance on the DC side, the current change between two sampling periods can be regarded as a disturbance and can be regarded as a constant value. The constant value can be considered as the average value of the inverter input current at two moments.

[0103] Then, the mathematical model of the AC side LC filter is established, and the differential equation of the AC side LC filter is:

[0104]

[0105] Among them, L and C are the inductance and capacitance of the AC side respectively, v i,αβ 、v C,αβ 、i L,αβ and i o,αβ They are respectively the inverter three-phase output voltage, three-phase capacitor voltage, three-phase inductor current value and three-phase output current value in the α-β two-phase coordinate system.

[0106] According to formula (6), the spatial state equation of the system can be obtained. Through the zero-order hold discretization method, the discrete time model of the AC side can be obtained as follows:

[0107]

[0108] in,

[0109]

[0110] Furthermore, the objective function establishment process of predictive control specifically includes:

[0111] For the inverter in the DC microgrid, its control goal is to ensure the voltage quality on the AC side while reducing the DC microgrid oscillation. Based on the above control goals, the established control objective function is:

[0112] G=λ dc G dc +λ v G v +λ i G i (9)

[0113] in,

[0114]

[0115] Among them, λ dc , i and λ v They are the control target items (DC item G dc , AC voltage term G v and the AC current term G i ), C represents the capacitance value on the AC side, w ref represents the reference angular frequency, They represent the reference values ​​of the DC side capacitor voltage, the α component of the AC side capacitor voltage, and the β component of the AC side capacitor voltage, respectively. Cα 、v Cβ Respectively represent the α and β components of the AC side capacitor voltage, i Cα 、i Cβ They represent the α and β components of the AC side inductor current respectively.

[0116] Furthermore, since the weight factor is a fixed value, the design process is relatively complicated and does not have adaptive capability. Therefore, this embodiment replaces the fixed weight factor with an adaptive weight function, so that the system can stabilize the DC microgrid while ensuring the voltage quality on the AC side.

[0117] Specifically, the error range is allowed first. It is worth noting that the priority of the AC side control target is higher than that of the DC side control target. When the system is stable, the error of each control target is within the allowable error range. At this time, the DC side voltage is stable, and the DC side weight factor selects a smaller value to ensure the AC side voltage quality; at the moment when the system is disturbed, the system oscillates greatly. At this time, the error of each control target will exceed the allowable error range, and the DC side weight selects a larger value, so that the DC microgrid can be quickly stabilized and the dynamic response speed of the system can be improved.

[0118] The adaptive weight function can increase with the increase of error, so that the system has a certain adaptive ability. In addition, in order to improve the quality of the AC side voltage when the system is stable, when the DC side error is 0, the DC weight factor is 0; when the AC side error is 0, the AC side adaptive weight factor maintains a certain initial value, increasing the proportion of AC weight when the system is stable, thereby improving the quality of the system output voltage.

[0119] The error value of each control target at time k is expressed as:

[0120]

[0121] The adaptive weight function of the DC side capacitor voltage is:

[0122]

[0123] The adaptive weight function of the AC side capacitor voltage is:

[0124]

[0125] The adaptive weight function of the AC side inductor current is:

[0126]

[0127] Where C represents the capacitance value on the AC side, w ref represents the reference angular frequency, They represent the reference values ​​of the DC side capacitor voltage, the α component of the AC side capacitor voltage, and the β component of the AC side capacitor voltage, respectively. dc , Δv C , Δi C They represent the actual error values ​​of the DC side capacitor voltage, AC side capacitor voltage, and AC side inductor current, respectively. allow_dc 、v allow_ac 、i allow_ac Indicates their allowable error value, v Cα 、v Cβ They represent the α and β components of the AC side capacitor voltage, respectively, v refα 、v refβrepresents the reference phase voltage, i Cα 、i Cβ They represent the α and β components of the AC side inductor current respectively.

[0128] This embodiment adopts a fixed-frequency processing method of zero voltage vector injection, adds a DC side control target on the basis of traditional model predictive control, designs a static-dynamic adaptive objective function, improves the adaptive ability of the system, and can stabilize the DC microgrid in a short time under large oscillations, and maintain good voltage quality on the AC side, thereby improving the stability and dynamic performance of the system.

[0129] Based on the same technical concept as above, this embodiment also proposes a microgrid oscillation suppression control system based on an adaptive static-dynamic model, such as Figure 5 As shown, the control system proposed in this embodiment includes:

[0130] A prediction module, which uses a pre-built prediction model to predict the DC side capacitor voltage value, the AC side three-phase capacitor voltage value, and the AC side three-phase inductor current value at the next moment based on the sampled DC side capacitor voltage value, the DC side inductor current value, the AC side three-phase capacitor voltage value, the AC side three-phase inductor current value, and the AC side three-phase output current value at the current moment;

[0131] An adaptive weight calculation module, which is used to calculate the weights of various control targets according to an adaptive weight function;

[0132] And, an objective function evaluation module, which establishes a control objective function by combining the predicted DC side capacitor voltage value, AC side three-phase capacitor voltage value and AC side three-phase inductor current value with each control target weight.

[0133] Furthermore, the control system proposed in this embodiment also includes:

[0134] The vector control module adopts a modulation method of zero voltage vector injection to modulate the voltage vector output by the control objective function to achieve fixed frequency control.

[0135] Embodiment 2:

[0136] In order to verify the effectiveness of the control method proposed in the above embodiment, this embodiment compares its performance with the traditional model predictive control method, and builds a model in Simulink to perform a series of simulation verifications. The experimental parameters are set as shown in Table 3:

[0137] Table 3 Simulation parameters

[0138]

[0139] First, the effectiveness of the fixed-frequency processing method for zero voltage vector injection proposed in the above embodiment is verified. On the basis of fixed-frequency processing, an objective function containing a fixed weight factor is used to evaluate each voltage vector and compared with the traditional model predictive control. A simulation time of 0.2s is selected, and the load parameter is 30Ω; to ensure that the zero vector can be inserted within one modulation cycle, the fixed-frequency reduction coefficient m is selected as 0.95; at 0.1s, the load jumps from 30Ω to 20Ω, and the dynamic response speed and steady-state performance under large oscillations are observed.

[0140] Design a switch count integration module. Within a fixed period of 0.02s, when the rising and falling edges of the switch tube driving waveform are monitored, the switch count is accumulated, that is, the switch tube is counted when it is turned on or off, and the accumulated value is cleared at the end of the period. The slope of the switch count integration curve can be used to determine whether the frequency is constant; Figure 6 As shown in (a), after the fixed frequency processing, the slope of the integral curve of the switch is a constant and the frequency is a fixed value; Figure 6 As shown in (b), the slope of the integral curve of the number of switching times under traditional MPC control is not fixed, and the frequency keeps changing.

[0141] Figure 7 (a) is the AC side output waveform and DC side waveform diagram when the fixed-frequency stabilization control method (fixed weight factor) proposed in this paper is adopted; Figure 7 (b) is the AC side output waveform and DC side waveform under traditional MPC control. After the load jump, Figure 7 The DC side voltage overshoot of (a) is 11.03V, and the response time is 6.28ms; Figure 7 The DC side voltage overshoot of (b) is 10.23V, and the response time is 5.823ms, which shows that after the fixed-frequency processing, the DC voltage and AC side capacitor voltage after the load change can be tracked in a short time, and the system remains stable.

[0142] Figure 8 (a) is the FFT analysis diagram of the output three-phase AC voltage when the fixed-frequency stabilization control method (fixed weight factor) proposed in this paper is adopted; Figure 8 (b) is the FFT analysis diagram of the output three-phase AC voltage under traditional MPC control. Figure 8As shown in the figure, when the zero vector injection fixed frequency method is adopted, the output voltage amplitude of the system is reduced compared with the traditional MPC, and the total harmonic distortion (THD) is reduced compared with the traditional MPC. This is because the proposed fixed frequency processing method inserts a zero vector of a fixed time in each modulation cycle, which increases the zero vector action time of the system. Since the voltage change rate generated by the zero vector is small and the voltage change rate generated by the non-zero vector is large, the proportion of the zero vector increases, resulting in a decrease in the system output voltage ripple and an increase in the output voltage steady-state error; through the above comparison, it is explained that when the zero vector injection fixed frequency method proposed in the above embodiment is adopted, the system can still achieve the stable control target.

[0143] Secondly, it is verified that the fixed-frequency stabilization control method proposed in the above embodiment can maintain the original steady-state performance and transient performance of the system. Next, an adaptive weight function is used instead of a fixed weight function to further improve the system performance. In order to achieve the control objectives of stabilizing the oscillation of the DC microgrid and ensuring the voltage quality on the AC side, when the oscillation on the DC side is large, the adaptive system can stabilize the oscillation on the DC side by increasing the DC ratio; when there is a large fluctuation on the AC side, the AC weight ratio can be increased to ensure the voltage quality on the AC side. Note that the priority of the control target on the AC side is higher than that on the DC side; taking the DC side as an example, when λ dc When the values ​​are 0, 0.3, 1 and 5 respectively, the changes in the DC side performance and AC side performance of the system are observed.

[0144] like Fig. 9 As shown, Fig. 9 (a)(b)(c)(d) are λ dc The DC side voltage waveform and AC side capacitor voltage waveform when is 0, 0.3, 1 and 5. By observing the waveforms, we can intuitively find that: Fig. 9 As shown in (a), when there is no DC side control target, large oscillations occur on the DC side. When the oscillations are too large, they will affect the voltage quality on the AC side and eventually cause system instability. Fig. 9 (b)(c)(d) are compared. As the DC weight factor increases, the DC side voltage stabilizes faster and the dynamic performance improves, but the AC side output voltage steady-state error increases, THD increases, and the steady-state performance decreases. Therefore, when the system is stable, the DC weight factor takes a smaller value to improve the system steady-state performance; when the system is disturbed, the DC weight takes a larger value to improve the system dynamic performance. The adaptive weight function proposed in this paper can complete this control task well.

[0145] The DC side adaptive weight function proposed in the above embodiment sets the maximum allowable error. When the maximum allowable error range is exceeded, the DC weight factor takes a larger value; within the allowable error range, the DC weight factor increases as the error increases. The AC side adaptive objective function is consistent with the design concept of the DC side weight factor. Since the AC side control target has a higher priority than the DC side control target, as shown in formulas (13) and (14), a certain initial value is set for the AC weight factor, that is, when the AC error is 0, the AC weight still maintains a large proportion; at the moment when the load jumps, the DC side voltage error is greater than the allowable error value, and the DC side stabilization speed at this time depends on the DC weight proportion at this time.

[0146]

[0147] Among them, ψ dc and ψ ac are the DC weight ratio and AC weight ratio respectively; set v allow_dc is 5, v allow_ac is 2, i allow_ac is 3, and observe the changes in the proportion of AC weight during the simulation process; Fig.10 As shown, when stable, the AC ratio is maintained at more than 90%, ensuring the steady-state performance of the AC side of the system; at the moment of load jump, the AC ratio decreases and the DC ratio increases, improving the response speed of the DC side and the dynamic performance of the system.

[0148] The improvement of the steady-state performance and dynamic performance of the system by the adaptive weight function proposed in the above embodiment is further verified. Fig.11 As shown, Fig.11 (a) is the AC side output waveform and DC side waveform when the constant frequency stabilization control method (adaptive weight function) proposed in this paper is adopted; Fig.11 (b) is the AC side output waveform and DC side waveform when the fixed frequency stabilization control method (fixed weight factor) proposed in this paper is used. After the load jump, Fig.11 (a) The DC side voltage overshoot is 6.96 V and the response time is 4.557 ms; Fig.11 (b) The DC side voltage overshoot is 11.03V and the response time is 6.28ms. After using the adaptive weight function instead of the fixed weight factor, the dynamic performance of the system is significantly improved. Compared with the traditional MPC, Figure 7 (b) The overshoot on the DC side is 10.23 V and the response time is 5.283 ms, which shows that the adaptive fixed-frequency model predictive control method proposed in this paper can effectively improve the dynamic performance of the system.

[0149] Next, the steady-state performance of the system is compared, such as Fig.12 As shown, Fig.12(a), (b), (c), and (d) are the FFT analysis diagrams of the AC side capacitor voltage before and after the load jump when the fixed-frequency stabilization control method (adaptive weight function) proposed in this paper is used, and before and after the load jump when the fixed-frequency stabilization control method (fixed weight factor) proposed in this paper is used. Fig.12 (a) Same Fig.12 (c) Compared with the fixed weight factor, after the adaptive weight function is used instead of the fixed weight factor, the voltage amplitude of the AC side capacitor increases from 109.1V to 109.6V, and the total harmonic distortion THD value does not change much. Fig.12 (b) Same Fig.12 (d) shows that after the load step, the system oscillation increases. When the adaptive weight function is used, the system self-adjusts according to the error, the voltage amplitude of the capacitor on the AC side is still 109.6V, and the THD value is slightly reduced. When the fixed weight factor is used, the oscillation increases, and the weight factor is a fixed value, so the system cannot make self-adjustments, the voltage amplitude of the capacitor on the AC side is reduced to 108.7V, and the THD value increases; this shows that the steady-state performance of the system is significantly improved after the adaptive weight function is used instead of the fixed weight factor.

[0150] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0151] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0152] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0153] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0154] The specific implementation methods described above further illustrate the purpose, technical solutions and beneficial effects of the present application in detail. It should be understood that the above description is only the specific implementation method of the present application and is not intended to limit the scope of protection of the present application. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application should be included in the scope of protection of the present application.

Claims

1. A microgrid oscillation suppression control method based on an adaptive static-dynamic model, characterized in that: The microgrid oscillation suppression control method includes: Using the pre-built prediction model, based on the sampled DC side capacitor voltage value, DC side inductor current value, AC side three-phase capacitor voltage value, AC side three-phase inductor current value and AC side three-phase output current value at the current moment, the DC side capacitor voltage value, AC side three-phase capacitor voltage value and AC side three-phase inductor current value at the next moment are predicted; The predicted DC side capacitor voltage value, AC side three-phase capacitor voltage value, AC side three-phase inductor current value and their expected value deviation are used as control targets, and the control target function is established by combining the weights of each control target calculated according to the adaptive weight function; A modulation method of zero voltage vector injection is adopted to modulate the voltage vector output by the control objective function to realize fixed frequency control.

2. A microgrid oscillation suppression control method based on an adaptive static-dynamic model according to claim 1, characterized in that: The prediction model building process specifically includes: The mathematical model of the DC side LC filter is established and expressed as: Among them, L dc , C dc are the DC side inductance and DC side capacitance respectively; v s 、v dc 、i pol 、i dc They are the DC side input voltage value, DC side capacitor voltage value, inverter input current value and DC side inductor current value respectively; The discrete time model of the DC side is: Among them, i pol_i and i pol_f are the inverter input current at time k and the inverter input current at time k+1, T s is the sampling period, v dc (k+1) and v dc (k) represents the DC link capacitor voltage value at the next moment and the DC link capacitor voltage value at the current moment respectively.

3. The microgrid oscillation suppression control method based on the adaptive static-dynamic model according to claim 2 is characterized in that: The prediction model building process also includes: The mathematical model of the AC side LC filter is established and expressed as: Among them, L and C are the inductance and capacitance of the AC side respectively, v i,αβ 、v C,αβ 、i L,αβ and i o,αβ They are the three-phase output voltage, three-phase capacitor voltage, three-phase inductor current value and three-phase output current value of the inverter in the α-β two-phase coordinate system respectively; Through the zero-order hold discretization method, the discrete time model of the AC side is obtained as follows: in, Among them, i L,αβ (k+1),i L,αβ (k) represents the three-phase inductor current value of the AC side at the next moment and the three-phase inductor current value of the AC side at the current moment respectively; v C,αβ (k+1),v C,αβ (k) respectively represent the three-phase capacitor voltage value on the AC side at the next moment and the three-phase capacitor voltage value on the AC side at the current moment.

4. A microgrid oscillation suppression control method based on an adaptive static-dynamic model according to any one of claims 1 to 3, characterized in that: The control objective function established is expressed as: G=λ dc G dc +λ v G v +λ i G i in, Among them, λ dc , i and λ v are the weight factors of each control target item, C represents the capacitance value on the AC side, and w ref represents the reference angular frequency, They represent the reference values ​​of the DC side capacitor voltage, the α component of the AC side capacitor voltage, and the β component of the AC side capacitor voltage, respectively. Cα 、v Cβ Respectively represent the α and β components of the AC side capacitor voltage, i Cα 、i Cβ They represent the α and β components of the AC side inductor current respectively.

5. The microgrid oscillation suppression control method based on an adaptive static-dynamic model according to claim 4 is characterized in that: The adaptive weight function includes: The adaptive weight function of the DC side capacitor voltage is: The adaptive weight function of the AC side capacitor voltage is: The adaptive weight function of the AC side inductor current is: in, v allow-dc 、v allow-ac 、i allow-ac They represent the allowable voltage error on the DC side, the allowable voltage error on the AC side, and the allowable current error on the AC side respectively.

6. The microgrid oscillation suppression control method based on an adaptive static-dynamic model according to claim 4 is characterized in that: The modulation method of zero voltage vector injection specifically includes: Reduce the original eight voltage vectors: V i * =V i ×m Among them, V i is the i+1th voltage vector, i=0,2,…7; m is the voltage vector reduction coefficient; A zero voltage vector of a fixed duration is inserted in each modulation cycle, so that the action time of the zero voltage vector is increased.

7. A microgrid oscillation suppression control system based on an adaptive static-dynamic model, characterized in that: The microgrid oscillation suppression control system comprises: A prediction module, wherein the prediction module uses a pre-built prediction model to predict the DC capacitor voltage value, the AC side three-phase capacitor voltage value, and the AC side three-phase inductor current value at the next moment based on the sampled DC side capacitor voltage value, the DC side inductor current value, the AC side three-phase capacitor voltage value, the AC side three-phase inductor current value, and the AC side three-phase output current value at the current moment; An adaptive weight calculation module, wherein the adaptive weight calculation module is used to calculate a control target weight according to an adaptive weight function; And, an objective function evaluation module, which uses the predicted DC side capacitor voltage value, AC side three-phase capacitor voltage value and AC side three-phase inductor current value and their expected value deviations as control targets, combines the weights of each control target, and establishes a control objective function.

8. A microgrid oscillation suppression control system based on an adaptive static-dynamic model according to claim 7, characterized in that: The microgrid oscillation suppression control system further includes: The vector control module adopts a modulation method of zero voltage vector injection to modulate the voltage vector output by the control objective function to achieve fixed frequency control.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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