Virtual synchronous machine control method considering harmonic wave and frequency stability

Abstract

The invention relates to the technical field of virtual synchronous motors, in particular to a virtual synchronous machine control method considering harmonic wave and frequency stability, which not only simplifies a voltage and current double-closed-loop control system, but also overcomes the defect of complex parameter adjustment of the traditional PI control by adopting a model prediction control strategy. And the harmonic content of the output network side current is obviously reduced, and the stability of the system is improved. And meanwhile, the response speed of the frequency is increased, so that the system can quickly adapt to dynamic change, and the overall control performance and operation efficiency are improved. The method also has good robustness and adaptability, and provides a new way for optimization of the energy storage system.

Description

Technical Field

[0001] The present invention relates to the technical field of virtual synchronous motors, and in particular to a virtual synchronous motor control method that takes harmonics and frequency stability into consideration. Background Art

[0002] With the widespread access of renewable energy to the power grid, traditional power grids are facing the problem of decreased stability due to the lack of sufficient inertia and damping. Although traditional virtual synchronous generator (VSG) technology can enhance the dynamic response of the power grid by simulating the inertia and damping characteristics of synchronous generators, its control strategy is mostly based on linear control theory, which is difficult to effectively deal with the nonlinearity and uncertainty of the power grid.

[0003] In addition, the conventional Sine Pulse Width Modulation (SPWM) control method requires complex dual-loop control, the PI parameters (Proportional Integral control parameters) are difficult to adjust, the harmonic content is high, and the frequency response performance is poor, which also leads to poor quality of voltage and current waveforms.

[0004] Based on the above reasons, the present invention designs a virtual synchronous machine control method that takes harmonics and frequency stability into consideration. By adopting a model predictive control strategy, the voltage and current dual closed-loop control system is simplified, the harmonic content of the output grid-side current is reduced, the stability of the system and the response speed of the frequency are improved, the overall control performance and operating efficiency are improved, and it also has good robustness and adaptability. Summary of the invention

[0005] The purpose of the present invention is to overcome the shortcomings of the prior art and provide a virtual synchronous machine control method taking harmonics and frequency stability into consideration. By adopting a model predictive control strategy, the voltage and current dual closed-loop control system is simplified, the harmonic content of the output grid-side current is reduced, the stability of the system and the response speed of the frequency are improved, the overall control performance and operating efficiency are improved, and it also has good robustness and adaptability.

[0006] In order to achieve the above object, the present invention provides a virtual synchronous machine control method considering harmonics and frequency stability, comprising the following steps: S1, determine the power angle of the virtual synchronous machine by solving the rotor motion equation and the active power frequency droop characteristic equation simultaneously, the virtual inertia and damping coefficient in the rotor motion equation are related to the angular velocity deviation and the angular velocity change rate; S2, realizing reactive power voltage control by establishing reactive power voltage droop characteristic of reactive power voltage droop characteristic equation, and taking the maximum absolute value of reactive power voltage regulated output voltage as the amplitude of virtual synchronous machine; S3, determining the three-phase voltage reference value by vector synthesis according to the power angle and amplitude, and determining the VSG output reference voltage and according to the three-phase voltage reference value; S4, determining a grid connection point voltage prediction value, an inductor current prediction value, and an inductor current reference value by establishing an LC filter model; S5, determining penalty items of third harmonic, fifth harmonic and seventh harmonic according to the predicted value of the inductor current, and determining penalty item of frequency stability according to the predicted value of the grid connection point voltage; S6, establishing a cost function through the contents determined in S3 to S5, and screening and outputting the optimal voltage vector through the cost function for controlling the VSG.

[0007] The formula for the rotor motion equation is: Formula 1: ; J is the virtual inertia, D is the damping coefficient, is the mechanical power, is the electromagnetic power, is the actual angular velocity, is the rate of change of angular velocity, is the rated angular velocity, is the angular velocity deviation, For the power angle.

[0008] The formula of the active power frequency droop characteristic equation is: Formula 2: ; is the mechanical power, Enter the reference value for active power, is the active power frequency droop control coefficient.

[0009] The formula of reactive power voltage droop characteristic equation is: Formula 3: ; Enter the reference value for reactive power, is the reactive power voltage droop control coefficient, The output voltage is regulated for reactive power voltage, is the rated voltage.

[0010] The specific formula for determining the three-phase voltage reference value in S3 is: Formula 4: ; , , is the three-phase voltage reference value, The output voltage amplitude is adjusted for reactive power voltage, For the power angle.

[0011] The specific content of S4 is: establish the state space model of the LC filter three-phase inverter in the system Cartesian coordinate system under the continuous domain, and predict the grid-connected point current and grid-side current according to the inductor current, grid-connected point voltage, inverter output current and inverter voltage vector at the current moment. The model is: Formula 5: ; L and C are filter inductance and capacitance respectively, and is the inductor current, and is the grid voltage, and are the d-axis component and q-axis component of the grid-side current; The model of formula 5 is discretized using the first-order Euler equation to obtain the inductor current prediction formula and the grid-connected point voltage prediction formula, and then the inductor current prediction value is obtained. and , and the predicted value of the grid connection point voltage and ; The calculation formula of the inductor current reference value in S4 is: Formula 6: ; , VSG is the output reference voltage. , is the inductor current reference value.

[0012] The discretization of the first-order Euler equation is as follows: When the sampling period is small enough, the continuous model is discretized based on the forward difference method to obtain the prediction model of the system: Formula 7: ; Formula 8: is the state variable of the discrete system; Formula 9: The input vector is obtained from the inverter voltage; Formula 10: is the disturbance vector; Formula 11: is the output vector, is the sampling period; The matrix A is: ; The matrix B is: ; matrix for: ; The matrix C is: .

[0013] The penalty terms for the third, fifth, and seventh harmonics in S5 are: Formula 12: ; is the fundamental frequency, is the angular frequency of the fundamental frequency, , , denote the penalty terms of the third harmonic, fifth harmonic, and seventh harmonic respectively; The penalty term formula for frequency stability is: Formula 13: ; is the penalty term for frequency stability.

[0014] The steps of S6 are: Based on the predicted value of the grid connection point voltage and the predicted value of the inductor current, a cost function is established in the form of a multi-objective value function. The cost function formula is: Formula 14: ; To take the absolute value of the variable in brackets, is the weight coefficient of the inductor current, is the weight coefficient of the harmonic penalty term, is the weight coefficient of the penalty term for frequency stability.

[0015] Screening and outputting the optimal voltage vector for controlling the VSG through the cost function includes: outputting the voltage vector corresponding to the minimum value of the cost function as the optimal voltage vector.

[0016] Compared with the prior art, the present invention has the following beneficial effects: The present invention adopts the model predictive control strategy, which not only simplifies the voltage and current dual closed-loop control system, overcomes the shortcomings of the traditional PI control parameter adjustment complexity, but also significantly reduces the harmonic content of the output grid-side current and improves the stability of the system. At the same time, the frequency response speed is enhanced, so that the system can adapt quickly in dynamic changes, and the overall control performance and operating efficiency are improved. The present invention also has good robustness and adaptability, and provides a new way to optimize the energy storage system. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 The figure is a flow chart of a virtual synchronous machine control method considering harmonics and frequency stability according to an embodiment of the present invention.

[0018] Figure 2 Schematic diagram of traditional VSG topology and control structure.

[0019] Figure 3 This is a block diagram of active frequency control according to an embodiment of the present invention.

[0020] Figure 4 4 is a reactive voltage control block diagram of an embodiment of the present invention.

[0021] Figure 5 Schematic diagram of the VSG topology and control structure according to an embodiment of the present invention.

[0022] Figure 6 FIG. 4 is a vector diagram of an inverter output voltage according to an embodiment of the present invention.

[0023] Figure 7 Simulation results of the virtual synchronous generator using traditional control method.

[0024] Figure 8 This is a simulation result diagram of a virtual synchronous generator using the method proposed in the present invention.

[0025] Fig. 9 Analysis diagram of simulation results using traditional control method for virtual synchronous generator.

[0026] Fig.10 This is an analysis diagram of simulation results of a virtual synchronous generator using the method proposed in the present invention. DETAILED DESCRIPTION

[0027] The present invention will now be further described with reference to the accompanying drawings.

[0028] See also Figures 1 to 10 ,This embodiment provides a virtual synchronous machine control method considering harmonics and frequency stability, S1, determines the power angle of the virtual synchronous machine by simultaneously solving the rotor motion equation and the active power frequency droop characteristic equation, and the virtual inertia and damping coefficient in the rotor motion equation are related to the angular velocity deviation and the angular velocity change rate; S2, realizing reactive power voltage control by establishing reactive power voltage droop characteristic of reactive power voltage droop characteristic equation, and taking the maximum absolute value of reactive power voltage regulated output voltage as the amplitude of virtual synchronous machine; S3, determining the three-phase voltage reference value by vector synthesis according to the power angle and amplitude, and determining the VSG output reference voltage and according to the three-phase voltage reference value; S4, determining a grid connection point voltage prediction value, an inductor current prediction value, and an inductor current reference value by establishing an LC filter model; S5, determining penalty items of third harmonic, fifth harmonic and seventh harmonic according to the predicted value of the inductor current, and determining penalty item of frequency stability according to the predicted value of the grid connection point voltage; S6, establishing a cost function through the contents determined in S3 to S5, and filtering and outputting the optimal voltage vector through the cost function for controlling the VSG, the optimal voltage vector being the voltage vector corresponding to the minimum value of the cost function.

[0029] The formula for the rotor motion equation is: Formula 1: ; J is the virtual inertia, D is the damping coefficient, is the mechanical power, is the electromagnetic power, is the actual angular velocity, is the rate of change of angular velocity, is the rated angular velocity, is the angular velocity deviation, For the power angle.

[0030] The formula of the active power frequency droop characteristic equation is: Formula 2: ; is the mechanical power, Enter the reference value for active power, is the active power frequency droop control coefficient.

[0031] The formula of reactive power voltage droop characteristic equation is: Formula 3: ; Enter the reference value for reactive power, is the reactive power voltage droop control coefficient, The output voltage is regulated for reactive power voltage, is the rated voltage.

[0032] The specific formula for determining the three-phase voltage reference value in S3 is: Formula 4: ; , , is the three-phase voltage reference value, The output voltage amplitude is adjusted for reactive power voltage, For the power angle.

[0033] The specific content of S4 is: establish the state space model of the LC filter three-phase inverter in the system Cartesian coordinate system under the continuous domain, and predict the grid-connected point current and grid-side current according to the inductor current, grid-connected point voltage, inverter output current and inverter voltage vector at the current moment. The model is: Formula 5: ; L and C are filter inductance and capacitance respectively, and is the inductor current, and is the grid voltage, and are the d-axis component and q-axis component of the grid-side current; The model of formula 5 is discretized using the first-order Euler equation to obtain the inductor current prediction formula and the grid-connected point voltage prediction formula, and then the inductor current prediction value is obtained. and , and the predicted value of the grid connection point voltage and ; The calculation formula of the inductor current reference value in S4 is: Formula 6: ; , VSG is the output reference voltage. , is the inductor current reference value.

[0034] The discretization of the first-order Euler equation is as follows: When the sampling period is small enough, the continuous model is discretized based on the forward difference method to obtain the prediction model of the system: Formula 7: ; Formula 8: is the state variable of the discrete system; Formula 9: The input vector is obtained from the inverter voltage; Formula 10: is the disturbance vector; Formula 11: is the output vector, is the sampling period; The matrix A is: ; The matrix B is: ; matrix for: ; The matrix C is: .

[0035] The penalty terms for the third, fifth, and seventh harmonics in S5 are: Formula 12: ; is the fundamental frequency, is the angular frequency of the fundamental frequency, , , denote the penalty terms of the third harmonic, fifth harmonic, and seventh harmonic respectively; The penalty term formula for frequency stability is: Formula 13: ; is the penalty term for frequency stability.

[0036] The model predictive control with harmonic penalty term performs better than traditional VSG control in suppressing harmonics, which is manifested in smoother grid-connected voltage and current waveforms, reduced harmonic components, more stable output of active power and reactive power, and significantly reduced fluctuations.

[0037] The steps of S6 are: Based on the predicted value of the grid-connected point voltage and the predicted value of the inductor current, a cost function is established in the form of a multi-objective value function. The multi-objective value function is one type of cost function. The cost function formula is: Formula 14: ; To take the absolute value of the variable in brackets, is the weight coefficient of the inductor current, is the weight coefficient of the harmonic penalty term, is the weight coefficient of the penalty term for frequency stability.

[0038] Screening and outputting the optimal voltage vector for controlling the VSG through the cost function includes: outputting the voltage vector corresponding to the minimum value of the cost function as the optimal voltage vector.

[0039] See also Figure 7 , Fig. 9 , the present invention only uses the simulation results of the traditional control method of the virtual synchronous generator. It can be seen that there are obvious harmonic components in the voltage waveform, which are manifested as small oscillations and irregularities on the waveform. The current waveform also shows obvious harmonic interference, and the waveform is relatively irregular. The active power fluctuates greatly, and the power output is unstable, reflecting that the control system's response to load changes is inaccurate. The reactive power fluctuates greatly, indicating that the system has poor control over voltage and phase.

[0040] See also Figure 8 , Fig.10 It is shown that the virtual synchronous generator adopts the method proposed by the present invention, the voltage waveform is smoother, the harmonic components are significantly reduced, and the waveform quality is significantly improved. The current waveform is also significantly improved, the harmonic interference is reduced, the waveform is more regular and smoother, and the fluctuation range is smaller. The active power fluctuation is significantly reduced, showing a more stable power output, the power output is more stable, and the system response is more accurate and faster. The high-frequency oscillation component of the reactive power is greatly reduced, the fluctuation range is significantly reduced, and the reactive power is more stable, reflecting that the system's control ability over voltage and phase has been significantly improved.

[0041] The above are only preferred embodiments of the present invention, which are only used to help understand the method and core ideas of the present application. The protection scope of the present invention is not limited to the above embodiments. All technical solutions under the concept of the present invention belong to the protection scope of the present invention. It should be pointed out that for ordinary technicians in this technical field, some improvements and modifications without departing from the principle of the present invention should also be regarded as the protection scope of the present invention.

[0042] The present invention adopts the model predictive control strategy, which not only simplifies the voltage and current dual closed-loop control system, but also overcomes the shortcomings of the traditional PI control parameter adjustment complexity. In addition, it also significantly reduces the harmonic content of the output grid-side current and improves the stability of the system. At the same time, it enhances the frequency response speed, enables the system to adapt quickly in dynamic changes, and improves the overall control performance and operating efficiency. The method has good robustness and adaptability, and provides a new way to optimize the energy storage system.

Claims

1. A virtual synchronous machine control method considering harmonics and frequency stability, characterized in that: The following steps are involved: S1, determining the power angle of the virtual synchronous machine by simultaneously solving the rotor motion equation and the active power frequency droop characteristic equation, wherein the virtual inertia and damping coefficient in the rotor motion equation are related to the angular velocity deviation and the angular velocity change rate; S2, realizing reactive power voltage control by establishing reactive power voltage droop characteristic of reactive power voltage droop characteristic equation, and taking the maximum absolute value of reactive power voltage regulated output voltage as the amplitude of the virtual synchronous machine; S3, determining a three-phase voltage reference value by vector synthesis according to the power angle and the amplitude, and determining a VSG output reference voltage and according to the three-phase voltage reference value; S4, determining a grid connection point voltage prediction value, an inductor current prediction value, and an inductor current reference value by establishing an LC filter model; S5, determining penalty items of third harmonic, fifth harmonic and seventh harmonic according to the predicted value of the inductor current, and determining penalty item of frequency stability according to the predicted value of the grid connection point voltage; S6, establishing a cost function based on the contents determined in S3 to S5, and screening and outputting an optimal voltage vector for controlling the VSG through the cost function.

2. The virtual synchronous machine control method considering harmonics and frequency stability according to claim 1, characterized in that: The formula of the rotor motion equation is: Formula 1: ; J is the virtual inertia, D is the damping coefficient, is the mechanical power, is the electromagnetic power, is the actual angular velocity, is the rate of change of angular velocity, is the rated angular velocity, is the angular velocity deviation, For the power angle.

3. The virtual synchronous machine control method considering harmonics and frequency stability according to claim 1, characterized in that: The formula of the active power frequency droop characteristic equation is: Formula 2: ; is the mechanical power, Enter the reference value for active power, is the active power frequency droop control coefficient.

4. The virtual synchronous machine control method considering harmonics and frequency stability according to claim 1, characterized in that: The formula of the reactive power voltage droop characteristic equation is: Formula 3: ; Enter the reference value for reactive power, is the reactive power voltage droop control coefficient, The output voltage is regulated for reactive power voltage, is the rated voltage.

5. The virtual synchronous machine control method considering harmonics and frequency stability according to claim 1, characterized in that: The specific formula for determining the three-phase voltage reference value in S3 is: Formula 4: ; , , is the three-phase voltage reference value, The output voltage amplitude is adjusted for reactive power voltage, For the power angle.

6. The virtual synchronous machine control method considering harmonics and frequency stability according to claim 1, characterized in that: The specific content of S4 is: establishing a state space model of the LC filter three-phase inverter in the system Cartesian coordinate system in the continuous domain, and predicting the grid-connected point current and the grid-side current according to the inductor current, grid-connected point voltage, inverter output current and inverter voltage vector at the current moment, and the model is: Formula 5: ; L and C are filter inductance and capacitance respectively, and is the inductor current, and is the grid voltage, and are the d-axis component and q-axis component of the grid-side current; The model of formula 5 is discretized using the first-order Euler equation to obtain the inductor current prediction formula and the grid connection point voltage prediction formula, and then the inductor current prediction value is obtained. and , and the predicted value of the grid connection point voltage and ; The calculation formula of the inductor current reference value in S4 is: Formula 6: ; , is the VSG output reference voltage, , is the inductor current reference value.

7. The virtual synchronous machine control method considering harmonics and frequency stability according to claim 6, characterized in that: The discretization process of the first-order Euler equation is specifically as follows: When the sampling period is small enough, the continuous model is discretized based on the forward difference method to obtain the prediction model of the system: Formula 7: ; Formula 8: is the state variable of the discrete system; Formula 9: The input vector is obtained from the inverter voltage; Formula 10: is the disturbance vector; Formula 11: is the output vector, is the sampling period; The matrix A is: ; The matrix B is: ; matrix for: ; The matrix C is: .

8. The virtual synchronous machine control method considering harmonics and frequency stability according to claim 1, characterized in that: The penalty term formulas for the third harmonic, fifth harmonic, and seventh harmonic described in S5 are: Formula 12: ; is the fundamental frequency, is the angular frequency of the fundamental frequency, , , denote the penalty terms of the third harmonic, fifth harmonic, and seventh harmonic respectively; The penalty term formula for the frequency stability is: Formula 13: ; is the penalty term for frequency stability.

9. The virtual synchronous machine control method considering harmonics and frequency stability according to claim 1, characterized in that: The steps of S6 are: Based on the grid connection point voltage prediction value and the inductor current prediction value, the cost function is established in the form of a multi-objective value function. The cost function formula is: Formula 14: ; To take the absolute value of the variable in brackets, is the weight coefficient of the inductor current, is the weight coefficient of the harmonic penalty term, is the weight coefficient of the penalty term of frequency stability; Screening and outputting the optimal voltage vector for controlling the VSG through the cost function includes: outputting the voltage vector corresponding to the minimum value of the cost function as the optimal voltage vector.

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