VSG control method based on parameter self-adaption and hybrid energy storage SOC adjustment

Abstract

The invention discloses a VSG control method based on parameter self-adaption and hybrid energy storage SOC adjustment. From the perspective of improving power grid frequency fluctuation under new energy grid connection, important factors such as an action mechanism of a virtual rotor angular frequency variation and a change rate, influence of rotational inertia and a damping coefficient on VSG power frequency response output characteristics, SOC balance adjustment of hybrid energy storage and the like are comprehensively considered; according to the method, the adaptive control of VSG parameters and the coordinated control of the hybrid energy storage SOC are realized, so that the purposes of reducing the response time and overshoot of VSG power frequency output, reducing the decrease amplitude of the SOC of the energy storage system and reducing the frequency fluctuation of a power grid in a transient process are achieved. Compared with a traditional VSG control method, the dynamic response capability of the VSG can be effectively enhanced, the service life of an energy storage system is prolonged, the transient stability of a power grid is improved, and the method has important guiding significance and engineering application value for design and optimization of a VSG controller.

Description

Technical Field

[0001] The present invention relates to the technical field of energy storage frequency modulation control, and in particular to a VSG control method based on parameter adaptation and hybrid energy storage SOC regulation. Background Art

[0002] In the context of building a new power system with new energy as the main body, photovoltaic power generation, as a renewable, pollution-free, easy-to-construct, economical and efficient new energy power generation method, has become an inevitable trend for large-scale construction and grid connection. However, photovoltaic power generation is subject to changes in light intensity and lacks power reserve capacity. It is directly connected to the grid through an inverter. The volatility and randomness of its power generation will cause the photovoltaic power generation system to be unable to meet the frequency regulation requirements of the power grid, and thus cannot quickly and fully respond to changes in power demand on the user side. In severe cases, it will also cause a large amount of abandoned light and power, and the stability and security of the power grid face huge challenges. In order to achieve the safety and transformation requirements of the new power system and ensure the stability of the power system, adding energy storage batteries to assist photovoltaic power generation can improve the primary frequency regulation capability of the power grid. At the same time, adding different types of energy storage batteries and giving full play to the advantages of various types of batteries in energy density and power density can achieve the goals of reducing costs, extending cycle life, optimizing output distribution, etc., and alleviate the problem of grid stability to a certain extent. In the research on the participation of energy storage batteries in grid frequency regulation, most of them only consider the stability requirements of the power grid itself, and rarely consider the state of charge (SOC) of the energy storage battery itself.

[0003] Hybrid energy storage assisted photovoltaic power generation to participate in frequency regulation is currently the mainstream technical means of primary frequency regulation. In order to effectively give play to the advantages of flexible regulation of hybrid energy storage, the virtual synchronous generator (VSG) control technology is introduced in the inverter control of the hybrid energy storage assisted photovoltaic power generation system to simulate the operating characteristics of the synchronous generator. It can realize the primary frequency regulation function while providing inertia and damping support for the system, effectively increase the inertia of the power grid, and reduce the frequency regulation time and overshoot. Among the many studies on the control methods of hybrid energy storage to improve the stable operation of the power grid, the improvement based on VSG control has become a research hotspot for new primary frequency regulation control methods. However, the selection of rotational inertia and damping coefficient is related to the stable operation of VSG. If the parameters are not selected properly, when the power dispatching instruction changes or load disturbance occurs, the active power and frequency will have large oscillations. Therefore, it is necessary to study an inverter control method that considers the SOC characteristics of the energy storage battery and the power-frequency response characteristics of the VSG at the same time to achieve efficient and stable control of the power system frequency. Summary of the invention

[0004] The purpose of the present invention is to provide a VSG control method based on parameter adaptation and hybrid energy storage SOC regulation, which can dynamically and real-time adjust the moment of inertia and damping coefficient of the VSG according to the output frequency and energy storage SOC. While improving the power-frequency response characteristics of the VSG, it can also achieve the control of the output power and SOC of the energy storage battery, thereby meeting the purpose of reducing the frequency fluctuation of the power grid during the transient process.

[0005] In order to achieve the above object, the technical solution adopted by the present invention is:

[0006] A VSG control method based on parameter adaptation and hybrid energy storage SOC regulation includes the following steps:

[0007] Step 1) Establish an inverter control system based on VSG, calculate the second-order transfer function of VSG input and output active power according to the VSG active-frequency and reactive-voltage control equations, and calculate the corresponding natural oscillation angular frequency ω t , damping coefficient ξ, overshoot σ and adjustment time t s .

[0008] Step 2), analyze and calculate the mechanism of the effect of the moment of inertia and damping coefficient in VSG on the power-frequency response characteristics of VSG, and combine the power angle curve and frequency oscillation curve of the actual synchronous generator to give the corresponding parameter selection principle.

[0009] Step 3), for a system connected to two types of energy storage batteries, respectively calculate the state of charge (SOC) of the energy storage batteries, and set the upper limit value (SOC) of the SOC according to the charge and discharge characteristics of different energy storage batteries. i,max and lower limit SOC i,min .

[0010] Step 4), according to the energy storage charge and discharge coefficient K E The relationship diagram with the change of energy storage SOC defines the SOC adjustment coefficient K1 of the two energy storage batteries in the charging state and the SOC adjustment coefficient K2 in the discharging state respectively; the defined SOC adjustment coefficient can change according to the characteristics and output of different types of energy storage.

[0011] Step 5), introduce the SOC weight coefficient. The larger the remaining SOC of the energy storage battery, the smaller the weight coefficient, and the weaker the control effect on its SOC in the VSG adaptive adjustment; the smaller the remaining SOC of the energy storage battery, the larger the weight coefficient, and the stronger the control effect on its SOC in the VSG adaptive adjustment; the value of the weight coefficient is mainly determined by the set SOC limit and the charge and discharge status.

[0012] Step 6), combining the SOC adjustment coefficients and SOC weight coefficients of the two energy storage batteries, combining the SOC weight coefficient with the SOC adjustment coefficient at a set ratio, and obtaining a new SOC adjustment coefficient K of the hybrid energy storage system SOC ;

[0013] Step 7), combining the SOC states, SOC adjustment coefficients and SOC weight coefficients of the two energy storage batteries, and according to the selection principles of the moment of inertia and the damping coefficient, the VSG-based adaptive hybrid energy storage SOC control equation is obtained, so that the moment of inertia and the damping coefficient can be adaptively changed according to the VSG virtual rotor angular frequency change Δω, the angular frequency change rate dω / dt and the hybrid energy storage SOC.

[0014] In one embodiment, the step 1) is based on the inverter control equation of VSG, which is expressed as

[0015]

[0016] Where J and D are the moment of inertia and damping coefficient of VSG respectively; ω and ω0 are the actual angular frequency and rated angular frequency corresponding to the VSG rotor respectively; P m , P e are the mechanical power and output power of VSG respectively; P ref k is the active power command value output by VSG; p is the proportional adjustment coefficient;

[0017] The second-order transfer function of VSG input and output active power is expressed as follows:

[0018]

[0019] The corresponding natural oscillation angular frequency ω t , damping coefficient ξ, overshoot σ and adjustment time t s It is expressed as follows:

[0020]

[0021] In the formula, ω n is the natural oscillation angular frequency of the virtual synchronous generator; E is the excitation voltage of the virtual synchronous generator; U is the port voltage of the virtual synchronous generator; Z is the impedance of the filter circuit of the virtual synchronous generator; s is the complex frequency variable in Laplace transform, K ω is the proportional adjustment coefficient.

[0022] In one embodiment, in step 2), the mechanism of the effect of the moment of inertia and damping coefficient in the VSG on the power-frequency response characteristics of the VSG is as follows:

[0023] The moment of inertia J of VSG determines the oscillation frequency in its power-frequency response process, and the damping coefficient D determines the oscillation attenuation rate in its power-frequency response; the selection of VSG moment of inertia J is determined by both the virtual rotor angular frequency change Δω and the change rate dω / dt; the selection of damping coefficient D is only determined by the virtual rotor angular frequency change Δω. Under different conditions, the selection principles of moment of inertia and damping coefficient are as follows:

[0024] When Δω>0: If dω / dt>0, Δω(dω / dt)>0, then J increases and D increases; if dω / dt<0, Δω(dω / dt)<0, then J decreases and D increases;

[0025] When Δω<0: If dω / dt<0, Δω(dω / dt)>0, then J increases and D increases; if dω / dt>0, Δω(dω / dt)<0, then J decreases and D increases.

[0026] In one embodiment, the step 4) is based on the energy storage charge and discharge coefficient K E The relationship diagram of the change of energy storage SOC, the SOC adjustment coefficients K1 and K2 of the two energy storage batteries under charging and discharging are shown as follows:

[0027]

[0028] In one embodiment, in step 5), a SOC weight coefficient is introduced, as shown in the following formula:

[0029]

[0030] In the formula, λ' represents the introduced SOC weight coefficient, SOC i is the current SOC of the i-th type of energy storage battery; P i is the output power of the i-th type of energy storage battery, SOC i,min , SOC i,max are the lower and upper limits of the SOC of the i-th type of energy storage battery, respectively, depending on the properties of the actual battery; λ' c and λ' d are the weight coefficients of energy storage charging and discharging respectively.

[0031] In one example, in step 6), the SOC adjustment coefficient K of the new hybrid energy storage system SOC As follows:

[0032] K SOC =K1+(1-λ)K2

[0033] Where λ is the weight coefficient after normalization of the weight coefficient λ', expressed as:

[0034]

[0035] Where λ'1 and λ'2 are the SOC weight coefficients of different energy storage batteries.

[0036] In one embodiment, the step 7) is based on the VSG adaptive hybrid energy storage SOC control equation as follows:

[0037]

[0038] Where, J0 and D0 are the moment of inertia and damping coefficient of VSG during stable operation, respectively; K j , K d are the adjustment coefficients of the moment of inertia and damping coefficient respectively; N j 、N d are the change thresholds of the moment of inertia and damping coefficient respectively; Δω is the change of angular frequency.

[0039] When the VSG power command undergoes a step, the moment of inertia and damping coefficient of the VSG will respond quickly as the frequency and frequency change rate change. At the same time, their values ​​take into account the SOC of the energy storage battery. When the energy storage SOC is insufficient, the energy storage output is reduced to avoid the SOC being lower than the minimum limit, ensuring that the SOC of the two energy storages are within a reasonable range, thereby achieving dynamic regulation of the power command and coordinated control of the energy storage.

[0040] Compared with the prior art, the present invention has the following beneficial effects:

[0041] (1) The present invention provides a VSG control method based on parameter adaptation and hybrid energy storage SOC adjustment, which realizes adaptive control of VSG parameters and coordinated control of hybrid energy storage SOC, thereby achieving the purpose of reducing the response time and overshoot of VSG power frequency output, reducing the decrease amplitude of energy storage system SOC, and reducing the frequency fluctuation of the power grid during transient process.

[0042] (2) The adaptive adjustment method of the moment of inertia and damping coefficient designed in the present invention takes into account the change amount and rate of change of the virtual rotor angular frequency, and selects based on the parameter selection principle, which has strong versatility. At the same time, the SOC of the energy storage battery is combined with the VSG parameters. While optimizing the power-frequency response characteristics of the VSG, the dynamic response capability of the energy storage battery is improved to ensure the safety of the operation of the energy storage system. Compared with the traditional VSG control method, the present invention can effectively enhance the dynamic response capability of the VSG, delay the operating life of the energy storage system, and improve the transient stability of the power grid. It has important guiding significance and engineering application value for the design and optimization of the VSG controller. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1This is a VSG control flow chart based on parameter adaptation and hybrid energy storage SOC adjustment.

[0044] Figure 2 This is the VSG active power-frequency control block diagram.

[0045] Figure 3 This is the VSG reactive power-voltage control block diagram.

[0046] Figure 4 It is the relationship diagram between energy storage charge and discharge coefficient and SOC.

[0047] Figure 5 This is the topology diagram of the system built.

[0048] Figure 6 This is the VSG rotation inertia change curve.

[0049] Figure 7 VSG damping coefficient variation curve.

[0050] Figure 8 is the VSG active power response curve.

[0051] Fig. 9 This is the VSG frequency response curve.

[0052] Fig.10 This is the SOC change curve of the lithium-ion battery.

[0053] Fig.11 This is the SOC change curve of the all-vanadium liquid flow battery.

[0054] Fig.12 This is the active power variation curve of lithium-ion battery.

[0055] Fig.13 This is the active power variation curve of all-vanadium liquid flow battery. DETAILED DESCRIPTION

[0056] See also Figure 1 , and describes the implementation modes of the present invention in detail with reference to the accompanying drawings.

[0057] 1. Analysis of the influence of moment of inertia and damping coefficient on VSG power-frequency response characteristics

[0058] The active power-frequency control equation in droop control is improved by using the mechanical motion equation of the synchronous motor, and the VSG inverter control equation with inertia and damping is obtained, as shown in equation (1):

[0059]

[0060] Where J and D are the moment of inertia and damping coefficient of VSG respectively; ω and ω0 are the actual angular frequency and rated angular frequency corresponding to the VSG rotor respectively; Pm , P e are the mechanical power and output power of VSG respectively; P ref k is the active power command value output by VSG; p is the proportional adjustment coefficient. According to the above mathematical relationship, we can get Figure 2 VSG active power-frequency control block diagram.

[0061] In VSG, the regulation of excitation current is usually converted into direct control of voltage amplitude by the integral link to achieve error-free following of the control loop voltage. The mathematical equation is established in combination with the reactive power droop relationship as shown in equation (2):

[0062]

[0063] In the formula, Q ref is the reference reactive power; Q is the actual reactive power; E m D is the virtual excitation potential amplitude output by VSG; q is the voltage regulation coefficient; U ref is the reference voltage; U out is the actual output voltage amplitude of the system; K is the integral coefficient.

[0064] This scheme cancels the no-load potential as the voltage reference, uses the ability of the integral link to eliminate static errors, trims the virtual potential deviation, further improves the control accuracy, and enhances the voltage's autonomous regulation capability. The specific structure is as follows: Figure 3 shown.

[0065] The damping coefficient and inertia link in VSG are studied to explore their influence on the power-frequency response characteristics of VSG. From the perspective of formula, qualitative analysis is carried out, and formula (3) can be obtained from formula (1):

[0066]

[0067] It can be seen that for the frequency response of VSG, when the numerator remains unchanged and the system is disturbed, resulting in a sudden change in frequency, the larger the moment of inertia J of VSG, the slower the rate of change of its frequency, and the longer it takes to recover to stability. However, considering that the inverter as a power electronic device does not have a large overload capacity, and a large moment of inertia will cause the frequency of the system to oscillate, the value of the moment of inertia J should not be too large in actual selection. Therefore, when the frequency fluctuates, the moment of inertia J can be appropriately increased to suppress the frequency fluctuation; when the frequency begins to recover, the moment of inertia J can be reduced to speed up the recovery of the frequency.

[0068] According to formula (1), and assuming that the output resistance of VSG is 0, the second-order transfer function of VSG input and output active power can be approximated as shown in formula (4), and the corresponding natural oscillation angular frequency ω can be obtained.t , damping coefficient ξ, overshoot σ and adjustment time t s As shown in formula (5):

[0069]

[0070] In the formula, ω n is the natural oscillation angular frequency of the virtual synchronous generator; E is the excitation voltage of the virtual synchronous generator; U is the port voltage of the virtual synchronous generator; Z is the impedance of the filter circuit of the virtual synchronous generator; s is the complex frequency variable in Laplace transform, K ω is the proportional adjustment coefficient.

[0071] It can be seen that when the power command is given and the proportional adjustment coefficient K ω When the moment of inertia J and the damping coefficient D are constant, the dynamic performance of the VSG is determined by the moment of inertia J and the damping coefficient D. When D is constant, the larger the J, the smaller the ξ, and the greater the σ and t s When J is constant, the larger D is, the larger ξ is, and the larger σ and t are. s The smaller the moment of inertia J is, the greater the oscillation will be. However, a larger moment of inertia J will cause the output active power to oscillate, thus destroying the stability of the system. Therefore, it can be concluded that the moment of inertia J of the VSG determines the oscillation frequency in its power response process, while the damping coefficient D determines the oscillation attenuation rate in its power response.

[0072] In summary, combined with the power angle curve and frequency oscillation curve of the actual synchronous generator, the selection of VSG moment of inertia J is determined by both the change amount and change rate of the virtual rotor angular frequency; while the selection of the damping coefficient D is only determined by the change amount of the virtual rotor angular frequency. Under different conditions, the selection principles of the moment of inertia and damping coefficient are shown in Table 1:

[0073] Table 1 Principles for selecting moment of inertia and damping coefficient

[0074] Δω dω / dt Δω(dω / dt) J D >0 >0 >0 Increase Increase >0 <0 <0 Reduce Increase <0 <0 >0 Increase Increase <0 >0 <0 Reduce Increase

[0075] 2. VSG parameter adaptive control strategy based on energy storage SOC

[0076] The selection principle of VSG moment of inertia and damping coefficient given in Table 1 does not take into account the energy storage battery processing constraints under actual working conditions and the distribution problem of energy storage SOC. In response to this, the present invention proposes an improved VSG adaptive control strategy based on energy storage SOC, which can dynamically adjust the moment of inertia and damping coefficient of VSG in real time according to the output frequency and energy storage SOC. While improving the power-frequency response characteristics of VSG, it can also realize the control of the output power and SOC of the energy storage battery.

[0077] Define the charge and discharge coefficient K of energy storage E , and its relationship with energy storage SOC is as follows Figure 4As shown. Among them, K c , K d are the coefficients corresponding to energy storage charging and discharging respectively. When the energy storage output power is negative, its charging coefficient curve is represented by K in the figure. c The red solid line; when the energy storage output power is positive, its discharge coefficient curve is the red solid line representing K in the figure. d blue dotted line.

[0078] based on Figure 4 The regular curve of energy storage SOC is shown in Figure 6. The SOC adjustment coefficients K1 and K2 of the two energy storage batteries under charging and discharging are shown in formula (6):

[0079]

[0080] Combination Figure 4 , formula (6) shows that: when the energy storage battery 1 or the energy storage battery 2 is in a discharging state and the SOC is insufficient, the smaller the SOC adjustment coefficient is, and at this time the SOC adjustment coefficient of the energy storage battery 2 or the energy storage battery 1 is larger, so that the power output of the energy storage battery 1 or the energy storage battery 2 is less, and the SOC decrease is smaller, avoiding the situation of over-discharge caused by too low SOC; when the energy storage battery 1 or the energy storage battery 2 is in a charging state and the SOC capacity is insufficient, the specific analysis is the same.

[0081] Taking into account the SOC of the energy storage battery 1 and the energy storage battery 2, as well as the influence of the VSG moment of inertia and damping coefficient, the present invention introduces the SOC weight coefficient. The larger the remaining SOC of the battery, the smaller the weight coefficient λ', and the weaker the control effect on its SOC in the VSG adaptive adjustment. The specific expression of the weight coefficient consisting of charging and discharging parts is shown in formula (2):

[0082]

[0083] In the formula, SOC i is the current SOC of the i-th type of energy storage battery; P i is the output power of the i-th type of energy storage battery. SOC i,min , SOC i,max are the lower and upper limits of the SOC of the i-th type of energy storage battery, respectively, depending on the properties of the actual battery; λ' c and λ' d are the weight coefficients of energy storage charging and discharging respectively.

[0084] Select a type of energy storage battery as the benchmark and normalize the weight coefficient λ'. The processed weight coefficient λ is shown in formula (6):

[0085]

[0086] Combining two energy storage batteries and VSG adaptive SOC control strategy, the SOC adjustment coefficient K of the energy storage system is redefined. SOC As shown in formula (3):

[0087] K SOC =λK1+(1-λ)K2 (9)

[0088] The method of the present invention can be applied to different types of energy storage batteries. According to the characteristics of different batteries, it is only necessary to appropriately change the SOC limit value in the formula.

[0089] Combining the above analysis and equations, as well as the parameter selection principles in Table 1, the VSG adaptive hybrid energy storage SOC control equation is designed as follows:

[0090]

[0091] Where, J0 and D0 are the moment of inertia and damping coefficient of VSG during stable operation, respectively; K j , K d are the adjustment coefficients of the moment of inertia and damping coefficient respectively; N j 、N d are the change thresholds of moment of inertia and damping coefficient respectively.

[0092] It can be seen from equations (3) and (4) that when the VSG power command undergoes a step change, the moment of inertia and damping coefficient of the VSG will respond quickly as the frequency and frequency change rate change. At the same time, their values ​​take into account the SOC of the energy storage battery. When the energy storage SOC is insufficient, the energy storage output is reduced to avoid the SOC being lower than the minimum limit, ensuring that the SOC of the two energy storages are within a reasonable range, thereby realizing dynamic regulation of the power command and coordinated control of the energy storage.

[0093] The method of the present invention can be applied to most transient fault conditions in the power system, such as: VSG input active power fluctuation, new energy output power fluctuation, grid-connected frequency fluctuation, grid-connected voltage fluctuation, grid-side load fluctuation, etc. It can accelerate the response speed of frequency modulation and reduce the power fluctuation peak value, which is helpful for the regulation and recovery of the power grid under transient fault conditions.

[0094] The application effect of the present invention is described in detail below in conjunction with simulation.

[0095] The simulation topology is established as Figure 5The parameters used are shown in Table 2. The two energy storage batteries selected are lithium-ion batteries and all-vanadium liquid flow batteries. The selected new energy photovoltaic model is a product of SunPower, model SPR-305E-WHT-D. The photovoltaic model consists of 20 groups of photovoltaic panels in parallel, and each group of panels consists of 10 separate photovoltaic cells in series. The maximum output power of each photovoltaic unit is 305.226W, and the corresponding open circuit voltage is 64.2V. Photovoltaic panel parameters T = 25 ° C, S = 1000W / m 2 , the corresponding maximum power is 61045.2W. The rated power of lithium battery and all-vanadium flow battery is 50kW, the capacity is 1000Ah, and the normal operating voltage is 1400V.

[0096] Table 2 Main circuit and VSG simulation parameters

[0097] parameter Value parameter Value <![CDATA[Filter inductor L f > 4mH <![CDATA[Rated angular frequency ω0]]> 314rad / s <![CDATA[Filter resistor R f > 0.05Ω <![CDATA[Steady-state value of moment of inertia J0]]> <![CDATA[0.2kg·m 2 ]]> <![CDATA[Filter capacitor C f > 10μF <![CDATA[Steady-state value of damping coefficient D0]]> 20N·m·s / rad <![CDATA[Line inductance L g > 1.2mH <![CDATA[Moment of inertia adjustment coefficient K j > 0.2 <![CDATA[Line resistance R g > 0.05Ω <![CDATA[Damping coefficient adjustment coefficient K d > 10 <![CDATA[DC bus voltage U dc > 1000V <![CDATA[Threshold N for change in moment of inertia j > 2 <![CDATA[Rated voltage U0]]> 380V <![CDATA[Damping coefficient change threshold N d > 0.1 <![CDATA[Rated frequency f0]]> 50Hz <![CDATA[Regulation coefficient K ω > 800

[0098] Set the initial value P of the active power input command of VSG ref The active power command is 200kW, and the active power command rises to 250kW in 2-4s, and then returns to 200kW. The initial SOC of the lithium-ion battery is set to 80%, and the initial SOC of the all-vanadium flow battery is set to 20%. Fig.10 , Fig.11 The active power and frequency response curves of VSG under three different strategies, the SOC change curves of lithium-ion batteries and all-vanadium liquid flow batteries, the active power change curves of lithium-ion batteries and all-vanadium liquid flow batteries, and the moment of inertia and damping coefficient change curves. Among them. Simulation analysis was performed according to three methods: Method 1, VSG control method with constant moment of inertia and damping coefficient; Method 2, VSG control method with adaptive moment of inertia and damping coefficient; Method 3, VSG control method based on parameter adaptation and hybrid energy storage SOC adjustment

[0099] (A) Verify the effectiveness of the VSG-based adaptive hybrid energy storage SOC control equation for the moment of inertia and damping coefficient.

[0100] Depend on Figure 6 , Figure 7 It can be seen that when the active power command changes, the moment of inertia and damping coefficient of the VSG will be adaptively adjusted accordingly. At 2-4s, the moment of inertia and damping coefficient change suddenly based on the initial value. Among them, at 2s, the moment of inertia of method 2 increases by 5.29kg·m 2 The moment of inertia of method 3 increases by 4.63 kg·m 2 At 4s, the moment of inertia of method 2 increased by 5.07kg·m 2 The moment of inertia of method 3 increases by 4.37 kg·m2 , and continued to adjust in the following period of time; for the damping coefficient, at 2s, the damping coefficient of strategy 2 increased by 21.94N·m·s / rad, and the damping coefficient of strategy 3 increased by 22.86N·m·s / rad. At 4s, the damping coefficient of strategy 2 increased by 23.13N·m·s / rad, and the damping coefficient of strategy 3 increased by 23.77N·m·s / rad.

[0101] (2) Verify the influence of the proposed VSG parameter adaptive control method on the output power-frequency characteristic curve.

[0102] The changes in VSG moment of inertia and damping coefficient are specifically reflected as follows: Figure 8 , Fig. 9 From the power frequency response curve, it can be seen that the overshoot of active power response under the three methods is 2.51%, 0.696%, and 0.215%, respectively, and the adjustment time is approximately 0.436s, 0.421s, and 0.339s, respectively. The overshoot of frequency response under the three methods is 1.09%, 0.71%, and 0.54%, respectively, and the adjustment time is approximately 0.604s, 0.511s, and 0.457s, respectively. In summary, compared with method 1, method 2 and method 3 have reduced overshoot and adjustment time in power frequency response, and compared with method 2, method 3 can further reduce overshoot and adjustment time.

[0103] (3) Verify the impact of the proposed VSG parameter adaptive control method on the SOC and output power of the energy storage battery.

[0104] Depend on Fig.10 , Fig.11 It can be seen that the SOC of the all-vanadium liquid flow battery is only 20%, which is in the over-discharge area, while the lithium-ion battery has sufficient remaining power. When the VSG adopts the control method proposed in the present invention, the SOC drop percentage of the all-vanadium liquid flow battery is reduced by 3.18% compared with the method 2. By appropriately increasing the moment of inertia and the damping coefficient, the all-vanadium liquid flow battery is prevented from having too low SOC, and the time when its SOC is lower than the lower limit is delayed. Fig.12 , Fig.13 It can be seen that when the all-vanadium liquid flow battery is in the over-discharge zone and the lithium-ion battery has sufficient remaining power, the control method proposed in the present invention can effectively slow down the rate of change of the output power of the all-vanadium liquid flow battery and ensure the safety of its operation.

[0105] In summary, the present invention takes into account the action mechanism of the change amount and rate of change of the virtual rotor angular frequency, the influence of the moment of inertia and damping coefficient on the power frequency response output characteristics of the VSG, the SOC balancing adjustment of the hybrid energy storage and other important factors from the perspective of improving the frequency fluctuation of the power grid under the connection of new energy, and realizes adaptive control of VSG parameters and coordinated control of the SOC of the hybrid energy storage, thereby achieving the purpose of reducing the response time and overshoot of the power frequency output of the VSG, reducing the decrease amplitude of the SOC of the energy storage system, and reducing the frequency fluctuation of the power grid during the transient process. Compared with the traditional VSG control method, the present invention can effectively enhance the dynamic response capability of the VSG, delay the operating life of the energy storage system, and improve the transient stability of the power grid. It has important guiding significance and engineering application value for the design and optimization of the VSG controller.

[0106] The above description is only a preferred example of the present invention, and is not intended to limit the present invention, and is not limited to the applications listed in the specification and implementation scheme, and can be applied to various fields suitable for the present invention. All other application examples obtained without any creative work within the spirit and principle of the present invention are within the protection scope of the present invention.

Claims

1. A VSG control method based on parameter adaptation and hybrid energy storage SOC regulation, characterized in that: The following steps are involved: Step 1) Establish an inverter control system based on VSG, calculate the second-order transfer function of VSG input and output active power according to the VSG active-frequency and reactive-voltage control equations, and calculate the corresponding natural oscillation angular frequency ω t , damping coefficient ξ, overshoot σ and adjustment time t s ; Step 2), analyze and calculate the mechanism of the effect of the moment of inertia and damping coefficient in the VSG on the power-frequency response characteristics of the VSG, and combine the power angle curve and frequency oscillation curve of the actual synchronous generator to give the corresponding parameter selection principle; Step 3), for a system connected to two types of energy storage batteries, respectively calculate the state of charge (SOC) of the energy storage batteries, and set the upper limit value (SOC) of the SOC according to the charge and discharge characteristics of different energy storage batteries. i,max and lower limit SOC i,min ; Step 4), according to the energy storage charge and discharge coefficient K E The relationship diagram with the change of energy storage SOC defines the SOC adjustment coefficient K1 of the two energy storage batteries in the charging state and the SOC adjustment coefficient K2 of the discharging state respectively; Step 5), introducing the SOC weight coefficient, the larger the remaining SOC of the energy storage battery, the smaller the weight coefficient, and the weaker the control effect on its SOC in the VSG adaptive adjustment; the smaller the remaining SOC of the energy storage battery, the larger the weight coefficient, and the stronger the control effect on its SOC in the VSG adaptive adjustment; Step 6), combining the SOC adjustment coefficients and SOC weight coefficients of the two energy storage batteries, combining the SOC weight coefficient with the SOC adjustment coefficient at a set ratio, and obtaining a new SOC adjustment coefficient K of the hybrid energy storage system SOC ; Step 7), combining the SOC states, SOC adjustment coefficients and SOC weight coefficients of the two energy storage batteries, and according to the selection principles of the moment of inertia and the damping coefficient, the VSG-based adaptive hybrid energy storage SOC control equation is obtained, so that the moment of inertia and the damping coefficient can be adaptively changed according to the VSG virtual rotor angular frequency change Δω, the angular frequency change rate dω / dt and the hybrid energy storage SOC.

2. A VSG control method based on parameter adaptation and hybrid energy storage SOC regulation according to claim 1, characterized in that: The step 1) is based on the inverter control equation of VSG, which is expressed as Where J and D are the moment of inertia and damping coefficient of VSG respectively; ω and ω0 are the actual angular frequency and rated angular frequency corresponding to the VSG rotor respectively; P m , P e are the mechanical power and output power of VSG respectively; P ref k is the active power command value output by VSG; p is the proportional adjustment coefficient; The second-order transfer function of VSG input and output active power is expressed as follows: The corresponding natural oscillation angular frequency ω t , damping coefficient ξ, overshoot σ and adjustment time t s It is expressed as follows: In the formula, ω n is the natural oscillation angular frequency of the virtual synchronous generator; E is the excitation voltage of the virtual synchronous generator; U is the port voltage of the virtual synchronous generator; Z is the impedance of the filter circuit of the virtual synchronous generator; s is the complex frequency variable in Laplace transform, K ω is the proportional adjustment coefficient.

3. A VSG control method based on parameter adaptation and hybrid energy storage SOC regulation according to claim 1, characterized in that: In step 2), the mechanism of the action of the moment of inertia and damping coefficient in the VSG on the power-frequency response characteristics of the VSG is as follows: The moment of inertia J of VSG determines the oscillation frequency in its power-frequency response process, and the damping coefficient D determines the oscillation attenuation rate in its power-frequency response; the selection of VSG moment of inertia J is determined by both the virtual rotor angular frequency change Δω and the change rate dω / dt; the selection of damping coefficient D is only determined by the virtual rotor angular frequency change Δω. Under different conditions, the selection principles of moment of inertia and damping coefficient are as follows: When Δω>0: If dω / dt>0, Δω(dω / dt)>0, then J increases and D increases; if dω / dt<0, Δω(dω / dt)<0, then J decreases and D increases; When Δω<0: If dω / dt<0, Δω(dω / dt)>0, then J increases and D increases; if dω / dt>0, Δω(dω / dt)<0, then J decreases and D increases.

4. A VSG control method based on parameter adaptation and hybrid energy storage SOC regulation according to claim 1, characterized in that: In step 4), according to the energy storage charge and discharge coefficient K E The relationship diagram of the change of energy storage SOC, the SOC adjustment coefficients K1 and K2 of the two energy storage batteries under charging and discharging are shown as follows:

5. The VSG parameter adaptive control method based on energy storage SOC according to claim 1 is characterized in that: In step 5), the SOC weight coefficient is introduced as shown in the following formula: In the formula, λ' represents the introduced SOC weight coefficient, SOC i is the current SOC of the i-th type of energy storage battery; P i is the output power of the i-th type of energy storage battery, SOC i,min , SOC i,max are the lower and upper limits of the SOC of the i-th type of energy storage battery, respectively, depending on the properties of the actual battery; λ c ' and λ d 'd are the weight coefficients of energy storage charging and discharging respectively.

6. The VSG parameter adaptive control method based on energy storage SOC according to claim 1 is characterized in that: In step 6), the SOC adjustment coefficient K of the new hybrid energy storage system SOC As follows: K SOC =λK1+(1-λ)K2 Where λ is the weight coefficient after normalization of the weight coefficient λ', expressed as: Where λ1' and λ2' are the SOC weight coefficients of different energy storage batteries.

7. The VSG parameter adaptive control method based on energy storage SOC according to claim 1 is characterized in that: The step 7) is based on the VSG adaptive hybrid energy storage SOC control equation, as follows: Where, J0 and D0 are the moment of inertia and damping coefficient of VSG during stable operation, respectively; K j , K d are the adjustment coefficients of the moment of inertia and damping coefficient respectively; N j 、N d are the change thresholds of the moment of inertia and damping coefficient respectively; Δω is the change of angular frequency.

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