Wind power storage self-adaptive power distribution control method considering battery SOC (State of Charge)

Abstract

The invention discloses a wind power energy storage self-adaptive power distribution control method considering a battery SOC, and the method comprises the steps: 1, adding an energy storage system in a direct-driven wind generating set, and building a wind power energy storage integrated system; 2, when the energy storage system participates in wind power distribution, introducing an SOC weight factor of an energy storage battery and power fluctuation of a grid-connected power reference value on the basis of a traditional low-pass filter algorithm, and forming a self-adaptive low-pass filter algorithm considering the power fluctuation and the SOC of the battery, and adaptive distribution of wind power is carried out on the energy storage system in the step 1 by adopting the adaptive low-pass filter algorithm. According to the power fluctuation and the SOC of the energy storage battery, the cut-off frequency of the low-pass filter algorithm is dynamically adjusted in a self-adaptive mode, self-adaptive distribution of the power is achieved, the power generated by the wind power system is smooth, meanwhile, the problems of over-charging and over-discharging of the energy storage battery caused by the adoption of the fixed cut-off frequency are solved, and the service life of the energy storage battery is prolonged.

Description

Technical Field

[0001] The present invention relates to the technical field of wind power generation control, and specifically, to an adaptive power distribution control method for wind power energy storage considering battery SOC. Background Art

[0002] With the transformation of the global energy structure and the improvement of environmental awareness, wind energy, as a clean and renewable energy source, has received extensive attention. The inherent intermittency and volatility of wind power generation pose challenges to the stable operation of the power system. Its power fluctuations not only affect the stability of the grid frequency and voltage but may also cause electrical equipment failures. In this context, studying the distribution of wind power and achieving smooth control of wind power fluctuations are of great significance for ensuring the reliability of new energy grid connection.

[0003] The energy storage system, with its bidirectional power regulation characteristics, can better participate in the distribution of wind power and demonstrates unique advantages in smoothing wind power fluctuations. As the core component of the energy storage system, the state of charge (SOC) of the energy storage battery directly affects the system performance and lifespan. If the energy storage battery is in a state of overcharge or over-discharge for a long time, it will lead to performance degradation or even permanent damage. Traditional wind power energy storage integrated systems generally adopt a low-pass filter algorithm with a fixed cut-off frequency. Although it can simply distribute the power and achieve smooth control of power fluctuations, it does not consider the change of the SOC of the energy storage battery, which is likely to cause overcharge and over-discharge problems of the energy storage battery and significantly shorten the service life of the energy storage battery.

[0004] The literature with the application number 202211245211.2 discloses an active power control method for a multi-energy complementary system based on hydropower and battery energy storage. The low-pass filter algorithm with a fixed cut-off frequency is used for power distribution of hybrid energy storage. It only considers stopping the output of the energy storage system when the battery is overcharged or over-discharged, and cannot dynamically adjust the cut-off frequency according to the SOC of the energy storage battery to enable self-recovery of the SOC of the energy storage battery. Summary of the Invention

[0005] Aiming at the deficiencies of the prior art, the technical problem to be solved by the present invention is to provide an adaptive power distribution control method for wind power energy storage considering battery SOC.

[0006] The technical solution of the present invention to solve the above technical problem is to provide an adaptive power distribution control method for wind power energy storage considering battery SOC, which is characterized in that the method includes the following steps:

[0007] Step 1: Add an energy storage system to a direct-drive wind turbine generator to establish a wind power energy storage integrated system;

[0008] Step 2: When the energy storage system participates in the wind power distribution, a SOC weight factor K of the energy storage battery is introduced on the basis of the traditional low-pass filter algorithm. SOC And the grid-connected power reference value P smooth of the power fluctuation, to form an adaptive low-pass filter algorithm considering power fluctuation and battery SOC, and adopt this adaptive low-pass filter algorithm for the energy storage system in Step 1 to perform the adaptive distribution of wind power.

[0009] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0010] (1) The present invention proposes an adaptive low-pass filter algorithm that simultaneously considers power fluctuation and the SOC of the energy storage battery to perform the adaptive distribution of wind power. According to the power fluctuation and the SOC of the energy storage battery, the cut-off frequency of the low-pass filter algorithm is adaptively and dynamically adjusted to achieve the adaptive distribution of power, which not only ensures that the power delivered from the wind power system to the power grid has less fluctuation, realizes the smoothing of the power generated by the wind power system, improves the utilization rate of wind energy and the stability of wind power grid connection, but also prevents the overcharging and over-discharging problems of the energy storage battery caused by using a fixed cut-off frequency, and improves the service life of the energy storage battery.

[0011] (2) The adaptive low-pass filter algorithm of the present invention adopts a dual-mode hierarchical control architecture, namely the SOC self-recovery control mode and the strong smoothing control mode, and adaptively and dynamically adjusts the cut-off frequency of the low-pass filter algorithm according to the real-time power fluctuation (i.e., the fluctuation of the grid-connected power reference value P smooth ), realizing the dynamic balance between the wind power smoothing effect and the protection of the battery life. When the power fluctuation does not meet the requirements, the lowest cut-off frequency is adopted to maximize the smoothing of the fluctuating power and ensure the stability of the grid-connected power.

[0012] (3) The present invention divides the battery SOC into five intervals, and dynamically adjusts the cut-off frequency during charging and discharging respectively on the premise of meeting the power fluctuation. During charging, the cut-off frequency is gradually increased as the SOC increases to prevent overcharging; during discharging, the cut-off frequency is gradually increased as the SOC decreases to avoid over-discharging.

[0013] (4) The present invention adjusts the energy storage charging and discharging priority through the SOC weight factor, reduces the redundant energy cycle, and improves the utilization rate of the energy storage battery. The dynamic adjustment strategy avoids the overcharging and over-discharging under extreme SOC, and reduces the capacity configuration of the energy storage battery.

[0014] (5) An energy storage system is added, and the two-way power regulation characteristic of the energy storage system is used to distribute the wind power, ensuring the smoothness of the output power of the wind power energy storage integrated system, thereby improving the stability and reliability of the wind power grid connection.

[0015] (6) The coordinated control strategy of the converter in the wind power energy storage integrated system designed by the present invention significantly improves the smoothness of the grid-connected power of the wind power system, enabling it to meet the technical specification requirements for grid connection. Description of the Drawings

[0016] Figure 1 It is a schematic diagram of the topological structure of the wind power energy storage integrated system of the present invention;

[0017] Figure 2 It is a schematic diagram of the control strategy of the energy storage side converter of the present invention;

[0018] Figure 3 It is a comparison diagram of the battery SOC of the adaptive low-pass filter algorithm and the low-pass filter algorithm in Embodiment 1 of the present invention;

[0019] Figure 4 It is a cut-off frequency diagram of the adaptive low-pass filter algorithm in Embodiment 1 of the present invention;

[0020] Figure 5 It is a power diagram of the adaptive low-pass filter algorithm and the low-pass filter algorithm allocated to the energy storage battery in Embodiment 1 of the present invention;

[0021] Figure 6 It is a power diagram of the adaptive low-pass filter algorithm and the low-pass filter algorithm allocated to the power grid in Embodiment 1 of the present invention. Detailed Embodiments

[0022] The following are specific embodiments of the present invention. The specific embodiments are only used to further illustrate the present invention in detail and do not limit the protection scope of the present invention.

[0023] The present invention provides a wind power energy storage adaptive power distribution control method considering battery SOC (hereinafter referred to as the method), which is characterized in that the method includes the following steps:

[0024] Step 1. To solve the impact of the intermittency and volatility of wind power generation on the power grid, an energy storage system is added to the direct-drive wind turbine generator set to establish a wind power energy storage integrated system;

[0025] Preferably, in Step 1, the wind power energy storage integrated system (as shown in Figure 1 ) is composed of a direct-drive wind turbine generator set and an energy storage system; the energy storage system adopts the topological structure configured on the DC side of the direct-drive wind turbine generator set, that is, the high-voltage side of the energy storage side converter is connected in parallel to the DC bus of the direct-drive wind turbine generator set.

[0026] Preferably, in Step 1, the direct-drive wind turbine generator set includes a wind turbine, a permanent magnet synchronous generator, a machine side converter, and a grid side converter; the energy storage system includes an energy storage battery and an energy storage side converter (a bidirectional buck-boost converter in this embodiment);

[0027] The functional realization of the wind power energy storage integrated system mainly depends on the coordinated control strategy of the converter, that is, the machine-side converter maximally obtains wind power, then the energy storage side converter distributes the wind power, and finally the grid-side converter transfers the allocated power to the power grid. Specifically: the machine-side converter rectifies the alternating current generated by the permanent magnet synchronous generator into direct current, and at the same time realizes maximum power point tracking through real-time adjustment to obtain the maximum wind power; the energy storage side converter distributes the wind power by controlling the bidirectional power regulation characteristics of the energy storage system: when it is detected that the output power is higher than the grid-connected power reference value, the energy storage system starts the charging mode to absorb the excess energy; when it is detected that the output power is lower than the grid-connected power reference value, the energy storage system switches to the discharging mode to supplement the energy gap; when it is detected that the output power is equal to the grid-connected power reference value, the energy storage system outputs normally; the grid-side converter maintains the constant direct current bus voltage through closed-loop control to ensure the stability of wind power transmission, and inverts the direct current into alternating current to send the smoothed wind power into the power grid.

[0028] Step 2: When the energy storage system participates in the wind power distribution, the SOC weight factor K of the energy storage battery is introduced on the basis of the traditional low-pass filter algorithm SOC and the grid-connected power reference value P smooth of the power fluctuation to form an adaptive low-pass filter algorithm considering power fluctuation and battery SOC, and the adaptive low-pass filter algorithm is used for the wind power adaptive distribution of the energy storage system in Step 1.

[0029] Preferably, in Step 2, the adaptive low-pass filter algorithm is specifically:

[0030] The high-frequency component of the wind power P wind has large fluctuations, and the low-frequency component has relatively stable fluctuations. By reasonably controlling the energy storage system, the power fluctuations in the high-frequency band can be effectively suppressed. The low-pass filter algorithm can effectively select signals below a certain frequency and block or attenuate signals above this frequency from passing through. This frequency is called the cut-off frequency f c . Therefore, the low-pass filter algorithm can be used to decompose the wind power P wind , allocate the low-frequency power to the power grid, and allocate the high-frequency power to the energy storage system; when using the low-pass filter algorithm to allocate the wind power P wind , there is:

[0031]

[0032] In formulas (1)-(2), P BESS is the power of the energy storage system; P wind is the wind power, that is, the power generated by the wind turbine; P smoothis the grid-connected power reference value, that is, the smoothed output power; T is the time constant, T = 1 / (2πf c ), f c is the cut-off frequency, and s is the Laplace operator;

[0033] From Equation (1), Equation (2), and T = 1 / (2πf c ), it can be seen that by adjusting the cut-off frequency f c , and then adjusting the time constant T, the grid-connected power reference value P smooth can be changed, and then the power P BESS of the energy storage system is changed, so as to realize the distribution of the wind power P wind to P smooth and P BESS ;

[0034] In order to study the influence of the time constant T on the distribution of the wind power P wind , with the time interval Δt as the sampling interval, discretizing Equation (1) and Equation (2) gives:

[0035]

[0036]

[0037] From Equation (3) and Equation (4), it can be seen that as the time constant T increases, the cut-off frequency f c becomes lower, and P smooth (t) is closer to P smooth (t - Δt), indicating that the smoothing effect of the wind power is better, thus reducing the impact on the power grid when the wind power is grid-connected; by increasing the time constant T, although the smoothing effect of the wind power can be improved, too low a cut-off frequency f c will cause the energy storage system to absorb or release more energy, thus increasing the capacity demand and burden of the energy storage system; therefore, when performing power smoothing, an appropriate cut-off frequency f c needs to be selected to balance the smoothing effect and the burden of the energy storage system;

[0038] Therefore, on the basis of the traditional low-pass filter algorithm, the SOC weight factor K SOC of the energy storage battery and the power fluctuation of the grid-connected power reference value P smooth are introduced for judgment, and an adaptive low-pass filter algorithm that simultaneously considers power fluctuation and battery SOC is formed to perform the adaptive distribution of the wind power P wind .

[0039] Preferably, in step 2, the adaptive low-pass filter algorithm includes a SOC self-recovery control mode and a strong smoothing control mode; at the beginning, the SOC self-recovery control mode is preferably adopted, and the initial cut-off frequency is obtained according to the current SOC of the battery, and the grid-connected power reference value P is calculated through the initial cut-off frequency smooth , and then the fluctuation of the grid-connected power reference value P smooth is judged in real time: when the fluctuation meets the requirements, the SOC self-recovery control mode of the energy storage system is maintained to prevent overcharging and over-discharging of the energy storage battery, and the corresponding cut-off frequency f is obtained according to the battery SOC c ; when the fluctuation does not meet the requirements, enter the strong smoothing control mode of the energy storage system, and preferably meet the requirements of the fluctuation of the grid-connected power reference value P smooth , and the cut-off frequency f c is adjusted to the set lowest cut-off frequency to ensure the smoothness of the power fed into the grid by the system and reduce the impact on the grid; after obtaining the corresponding cut-off frequency f c , the cut-off frequency f is converted into the time constant T through the formula T = 1 / (2πf c ), and then the time constant T is substituted into equation (1) to obtain the smoothed grid-connected power reference value P c ; the frequency domain characteristics of the low-pass filter algorithm are reconstructed through the time constant T updated in real time, so that the grid-connected power reference value P smooth can be dynamically adjusted according to its own fluctuation and the SOC of the energy storage battery, and finally the adaptive allocation of the wind power P smooth to P wind and P smooth and P BESS is realized.

[0040] Preferably, in step 2, in the SOC self-recovery control mode, the adjustment rule of the cut-off frequency f c is as follows:

[0041] f c = f c.min + K SOC (f c.max - f c.min ) (5)

[0042] In equation (5), f c.min and f c.max are the set lowest cut-off frequency and highest cut-off frequency, which are obtained by analyzing the amplitude-frequency characteristics of historical wind power; K SOC is the SOC weight factor; therefore, the cut-off frequency f SOC can be dynamically adjusted by dynamically adjusting the SOC weight factor K c ;

[0043] According to the different charge and discharge capabilities of the energy storage battery in different SOC intervals, the SOC is divided into five intervals; within different SOC intervals of the energy storage battery, the value of the SOC weighting factor K SOC is different; in order to enable the self-recovery of the SOC of the energy storage battery, make the battery operate in the normal charge and discharge area for a long time, and prevent overcharging and over-discharging of the battery, it is necessary to gradually increase the SOC weighting factor K SOC as the SOC increases during charging, and then gradually increase the cut-off frequency f c to prevent overcharging; during discharging, as the SOC decreases, gradually increase the SOC weighting factor K SOC and then gradually increase the cut-off frequency f c to prevent over-discharging; as shown in Equations (6) and (7):

[0044] During charging:

[0045]

[0046] During discharging:

[0047]

[0048] According to Equations (6) and (7), when the SOC is in the normal interval, the SOC weighting factor K SOC is a constant, and at this time, the power is distributed according to the fixed cut-off frequency f c ; when the SOC is in the lower interval or the higher interval, the value of the SOC weighting factor K SOC is changed in the form of a parabola; when the SOC is in the overcharge interval or the over-discharge interval, the value of the SOC weighting factor K SOC is adjusted so that the cut-off frequency is in the maximum or minimum state.

[0049] Preferably, in step 2, in the strong smoothing control mode, the adjustment rule of the cut-off frequency f c is:

[0050] f c = f c.min (8)

[0051] In Equation (8), f c.min is the set minimum cut-off frequency, which is obtained by performing amplitude-frequency characteristic analysis on the historical wind power.

[0052] Example 1:

[0053] To verify the effectiveness of the control strategy, a single direct-drive wind power energy storage power generation system model was built based on the MATLAB / Simulink simulation platform. The power of the generator is 5 kW, the capacity of the energy storage battery is 400 Wh, and the fixed cut-off frequency adopted by the traditional low-pass filter algorithm is 0.02 Hz. Simulation analysis was carried out on both of them.

[0054] It can be seen from Figure 3 that compared with the low-pass filter algorithm with a fixed cut-off frequency, when using the adaptive low-pass filter algorithm, the change range of the power distribution control SOC with a fixed cut-off frequency is between 10% and 88%, while the change range of SOC when using the adaptive low-pass filter algorithm is between 22% and 79%. It can better prevent overcharging and over-discharging of the battery and has the SOC self-recovery function, enabling the battery to operate in the normal area for a longer time. At this time, the cut-off frequency of the adaptive low-pass filter algorithm is as Figure 4 shown. It can be seen that this strategy can dynamically adjust the cut-off frequency according to SOC, proving the effectiveness of the proposed strategy.

[0055] It can be seen from Figure 5 and Figure 6 that the use of the adaptive low-pass filter algorithm can reduce the capacity of the battery, and the power fluctuations between the two are not much different, indicating that the present invention not only ensures the reduction of power fluctuations but also ensures the normal SOC of the energy storage battery, proving the effectiveness of the proposed method.

[0056] What is not described in the present invention applies to the prior art.

Claims

1. A wind power storage adaptive power distribution control method considering battery SOC, characterized in that: The method comprises the following steps: Step 1: Add an energy storage system to the direct-drive wind turbine generator set to establish an integrated wind power and energy storage system; Step 2: When the energy storage system participates in wind power distribution, the SOC weight factor K of the energy storage battery is introduced based on the traditional low-pass filter algorithm. SOC And the grid power reference value P smooth The power fluctuation is formed to form an adaptive low-pass filter algorithm that considers the power fluctuation and the battery SOC, and the adaptive low-pass filter algorithm is used for the energy storage system in step 1 to perform adaptive distribution of wind power.

2. The wind power energy storage adaptive power distribution control method considering battery SOC according to claim 1 is characterized in that: In step 1, the wind power energy storage integrated system consists of a direct-drive wind turbine generator set and an energy storage system; the high-voltage side of the energy storage side converter is connected in parallel to the DC bus of the direct-drive wind turbine generator set.

3. The wind power energy storage adaptive power distribution control method considering battery SOC according to claim 1 is characterized in that: In step 1, the direct-drive wind turbine generator set includes a wind turbine, a permanent magnet synchronous generator, a machine-side converter and a grid-side converter; the energy storage system includes an energy storage battery and an energy storage-side converter; The function of the wind power and energy storage integrated system is to obtain the maximum possible wind power through the machine-side converter, then the energy storage-side converter distributes the wind power, and finally the grid-side converter transfers the distributed power to the grid.

4. The wind power storage adaptive power distribution control method considering battery SOC according to claim 3 is characterized in that: In step 1, the functions of the wind power energy storage integrated system are specifically implemented as follows: the machine-side converter rectifies the AC power generated by the permanent magnet synchronous generator into DC power, and realizes maximum power point tracking through real-time adjustment to obtain the maximum wind power; the energy storage-side converter distributes wind power by controlling the bidirectional power regulation characteristics of the energy storage system: when it is detected that the output power is higher than the grid-connected power reference value, the energy storage system starts the charging mode to absorb excess energy; when it is detected that the output power is lower than the grid-connected power reference value, the energy storage system switches to the discharge mode to supplement the energy gap; when it is detected that the output power is equal to the grid-connected power reference value, the energy storage system outputs normally; the grid-side converter maintains a constant DC bus voltage through closed-loop control to ensure the stability of wind power transmission, and inverts DC power into AC power, and sends the smoothed wind power into the grid.

5. The wind power storage adaptive power distribution control method considering battery SOC according to claim 1 is characterized in that: In step 2, the adaptive low-pass filter algorithm is specifically: The low-pass filter algorithm is used to calculate the wind power P wind Decompose the low-frequency power to the grid and the high-frequency power to the energy storage system; use the low-pass filter algorithm to filter the wind power P wind When allocating: In formula (1)-(2), P BESS is the power of the energy storage system; P wind is wind power; P smooth is the grid-connected power reference value; T is the time constant, T = 1 / (2πf c ), f c is the cutoff frequency, s is the Laplace operator; From equation (1), equation (2) and T = 1 / (2πf c ) It can be seen that by adjusting the cut-off frequency f c , and then adjust the time constant T to change the grid power reference value P smooth , which in turn changes the energy storage system power P BESS , so as to realize the wind power P wind Assign to P smooth and P BESS ; In order to study the effect of time constant T on wind power P wind The influence of the distribution, taking the time interval Δt as the sampling interval, discretizes equations (1) and (2) to obtain: From equations (3) and (4), we can see that as the time constant T increases, the cutoff frequency f c The lower the P smooth (t) is closer to P smooth (t-Δt), indicating that the wind power smoothing effect is better; when performing power smoothing, it is necessary to select a suitable cut-off frequency f c , to balance the smoothing effect and the burden on the energy storage system; Therefore, the SOC weight factor K of the energy storage battery is introduced based on the traditional low-pass filter algorithm. SOC And the grid power reference value P smooth The power fluctuation is used to judge, and an adaptive low-pass filter algorithm that considers both power fluctuation and battery SOC is formed to calculate the wind power P wind Adaptive allocation.

6. The wind power storage adaptive power distribution control method considering battery SOC according to claim 5 is characterized in that: In step 2, the adaptive low-pass filter algorithm includes the SOC self-recovery control mode and the strong smoothing control mode; the SOC self-recovery control mode is preferentially used at the beginning, and the initial cutoff frequency is obtained according to the current battery SOC, and the grid-connected power reference value P is calculated by the initial cutoff frequency. smooth , and then the grid power reference value P smooth Real-time judgment of fluctuations: When the fluctuations meet the requirements, the SOC self-recovery control mode of the energy storage system is maintained, and the corresponding cutoff frequency f is obtained according to the battery SOC c When the fluctuation does not meet the requirements, the energy storage system enters the strong smoothing control mode, giving priority to meeting the grid-connected power reference value P smooth The fluctuation requirement, cut-off frequency f c Adjust to the set minimum cutoff frequency; get the corresponding cutoff frequency f at this time c Then, through the formula T = 1 / (2πf c ) Set the cut-off frequency f c Convert it into a time constant T, and then substitute the time constant T into formula (1) to obtain the smoothed grid-connected power reference value P smooth ; Reconstruct the frequency domain characteristics of the low-pass filter algorithm through the real-time updated time constant T, so that the grid-connected power reference value P smooth It can dynamically adjust according to its own fluctuations and the SOC of the energy storage battery, and finally achieve wind power P wind P smooth and P BESS Adaptive allocation.

7. The wind power energy storage adaptive power distribution control method considering battery SOC according to claim 6 is characterized in that: In step 2, when the SOC self-recovery control mode is in progress, the cut-off frequency f c The adjustment rules are: f c =f c.min +K SOC (f c.max -f c.min )(5) In formula (5), f c.min and f c.max are the minimum cutoff frequency and the maximum cutoff frequency, which are obtained by analyzing the amplitude-frequency characteristics of historical wind power; K SOC is the SOC weight factor; therefore, the SOC weight factor K can be adjusted dynamically SOC To dynamically adjust the cutoff frequency f c ; According to the different charging and discharging capabilities of energy storage batteries in different SOC intervals, SOC is divided into five intervals; in different energy storage battery SOC intervals, the SOC weight factor K SOC The value of is different; when charging, as the SOC increases, the SOC weight factor K gradually increases. SOC , and then gradually increase the cut-off frequency f c , to prevent overcharging; during discharge, as the SOC decreases, the SOC weight factor K is gradually increased. SOC , and then gradually increase the cut-off frequency f c , to prevent over-discharge; as shown in equations (6) and (7): While charging: When discharging: According to equations (6) and (7), when SOC is in the normal range, the SOC weight factor K SOC is a constant, at this time according to the fixed cutoff frequency f c Perform power distribution; when the SOC is in a lower range or a higher range, change the SOC weight factor K in the form of a parabola SOC When the SOC is in the overcharge range or over-discharge range, adjust the SOC weight factor K SOC value to make the cutoff frequency at the maximum or minimum state.

8. The wind power storage adaptive power distribution control method considering battery SOC according to claim 6 is characterized in that: In step 2, in strong smoothing control mode, the cutoff frequency f c The adjustment rules are: f c =f c.min (8) In formula (8), f c.min is the lowest cut-off frequency to be set, which is obtained by analyzing the amplitude-frequency characteristics of historical wind power.

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