Wind power prediction precision control method based on single-machine direct current side hybrid energy storage

Abstract

The invention provides a wind power prediction precision control method based on single-machine direct-current side hybrid energy storage, which is characterized in that the direct-current bus sides of fan converters of n wind generator sets of a wind power plant are merged into hybrid energy storage, and the hybrid energy storage comprises an electrochemical energy storage system and a super-capacitor energy storage system; acquiring a total charge-discharge power target value of the hybrid energy storage and charge state data of the electrochemical energy storage systems and the super-capacitor energy storage systems corresponding to the n wind generator sets at the current time node, and calculating charge-discharge target power of each hybrid energy storage according to the charge state data; the actual total power of the wind power plant is dynamically regulated and controlled within a deviation limit value by controlling each wind turbine generator set of the wind power plant to generate power according to the optimal power and controlling mixed energy storage tracking charging and discharging target power merged into the direct current bus side corresponding to the n wind turbine generator sets, and the condition that the wind power prediction deviation exceeds the limit and is examined and penalty is caused is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of wind power generation, and in particular to a method, device, electronic equipment and storage medium for controlling wind power prediction accuracy based on hybrid energy storage on the DC side of a single machine. Background Art

[0002] As the global demand for clean energy increases, wind power, as a green and renewable energy, is gradually becoming an important part of the energy structure. Unlike conventional energy, wind energy has the characteristics of randomness, volatility and intermittency, and the output of wind power is unstable. With the large-scale grid connection of wind power, it will inevitably bring challenges to the dispatching and stable operation of the power grid. Therefore, accurate prediction of wind power is particularly important.

[0003] In the relevant technology, wind power prediction is mainly divided into three categories: physical method, statistical method and combined method. The physical method is based on meteorology and the working principle of wind turbines. It establishes a mathematical model and considers physical factors such as wind speed, wind direction, temperature, air pressure, topography, wind turbine characteristics, etc. to predict power output; the statistical method is based on the analysis and research of historical statistical data and numerical weather forecast (NWP) data, establishes a mapping relationship between NWP data and wind farm output power, and mines the laws and trends in the data for prediction; the combined method combines physical methods and statistical methods, and comprehensively utilizes the advantages of both to improve the accuracy and reliability of wind power prediction. However, regardless of the type of method, the random fluctuations inherent in wind energy itself make the predicted power still have a large deviation from the actual results, resulting in frequent assessments and fines for wind farms. Summary of the invention

[0004] The present invention aims to solve one of the technical problems in the related art at least to a certain extent.

[0005] To this end, the first purpose of the present invention is to propose a wind power prediction accuracy control method based on a single-machine DC side hybrid energy storage to ensure that the actual total power generated by the wind farm is within the deviation limit, thereby reducing the situation of being assessed and fined due to excessive wind power prediction deviation.

[0006] The second object of the present invention is to provide a wind power prediction accuracy control device based on single-machine DC side hybrid energy storage.

[0007] A third objective of the present invention is to provide an electronic device.

[0008] A fourth object of the present invention is to provide a non-transitory computer-readable storage medium storing computer instructions.

[0009] To achieve the above-mentioned purpose, the first embodiment of the present invention proposes a wind power prediction accuracy control method based on a single-machine DC-side hybrid energy storage, wherein the DC bus side of the wind turbine converter of n wind turbines in the wind farm is integrated with the hybrid energy storage, and the hybrid energy storage includes an electrochemical energy storage system and a supercapacitor energy storage system, and the method includes:

[0010] The total charging and discharging power target value of the hybrid energy storage is converted to Decomposed into the total charging and discharging target power of the electrochemical energy storage system and the total charging and discharging target power of the supercapacitor energy storage system

[0011] According to the state of charge SOC of the electrochemical energy storage system corresponding to each wind turbine B,i And the state of charge SOC of the supercapacitor energy storage system S,i as well as and Determine the charge and discharge limit coefficient K of each electrochemical energy storage system and supercapacitor energy storage system B,i and K S,i , and according to the K B,i and K S,i , calculate the charge and discharge participation factor PF of each electrochemical energy storage system and supercapacitor energy storage system B,i and PF S,i ;

[0012] According to the PF B,i and PF S,i , calculate the charge and discharge distribution power P of the electrochemical energy storage system and the supercapacitor energy storage system B,i (j) and P S,i (j) The maximum charging and discharging power of the electrochemical energy storage system and the supercapacitor energy storage system is limited to P B,i (j) and P S,i (j) to obtain the target power of charge and discharge and

[0013] By controlling each wind turbine in the wind farm to generate power at the optimal power and controlling the hybrid energy storage tracking system connected to the DC bus side of n wind turbines and Dynamically control the total actual power generated by the wind farm to be within the deviation limit.

[0014] To achieve the above-mentioned purpose, the second embodiment of the present invention proposes a wind power prediction accuracy control device based on a single-machine DC-side hybrid energy storage, wherein the DC bus side of the wind turbine converter of n wind turbines in the wind farm is integrated with the hybrid energy storage, and the hybrid energy storage includes an electrochemical energy storage system and a supercapacitor energy storage system, and the device includes:

[0015] The decomposition module is used to convert the total charging and discharging power target value of the hybrid energy storage into Decomposed into the total charging and discharging target power of the electrochemical energy storage system and the total charging and discharging target power of the supercapacitor energy storage system

[0016] The first calculation module is used to calculate the state of charge SOC of the electrochemical energy storage system corresponding to each wind turbine group. B,i And the state of charge SOC of the supercapacitor energy storage system S,i as well as and Determine the charge and discharge limit coefficient K of each electrochemical energy storage system and supercapacitor energy storage system B,i and K S,i , and according to the K B,i and K S,i , calculate the charge and discharge participation factor PF of each electrochemical energy storage system and supercapacitor energy storage system B,i and PF S,i ;

[0017] The second calculation module is used to calculate the B,i and PF S,i , calculate the charge and discharge distribution power P of the electrochemical energy storage system and the supercapacitor energy storage system B,i (j) and P S,i (j) The maximum charging and discharging power of the electrochemical energy storage system and the supercapacitor energy storage system is limited to P B,i (j) and P S,i (j) to obtain the target power of charge and discharge and

[0018] The control module is used to control the wind turbines in the wind farm to generate electricity at the optimal power and control the hybrid energy storage tracking system connected to the DC bus side of the n wind turbines. and Dynamically control the total actual power generated by the wind farm to be within the deviation limit.

[0019] To achieve the above-mentioned purpose, the third aspect of the present invention proposes an electronic device, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the method described in the first aspect.

[0020] In order to achieve the above-mentioned purpose, the fourth aspect of the present invention proposes a non-transitory computer-readable storage medium storing computer instructions, where the computer instructions are used to enable the computer to execute the method described in the first aspect.

[0021] The embodiments of the present invention provide a method, device, electronic device and storage medium for controlling wind power prediction accuracy based on hybrid energy storage on the DC side of a single machine. The DC bus side of the wind turbine converter of n wind turbines in a wind farm is connected to the hybrid energy storage, and the hybrid energy storage includes an electrochemical energy storage system and a supercapacitor energy storage system. The total charging and discharging power target value of the hybrid energy storage and the charge state data of the electrochemical energy storage system and the supercapacitor energy storage system corresponding to the n wind turbines at the current time node are obtained, and the charging and discharging target power of each hybrid energy storage is calculated according to the charge state data; by controlling each wind turbine in the wind farm to generate electricity at the optimal power and controlling the hybrid energy storage connected to the DC bus side of the n wind turbines to track the charging and discharging target power, the actual total power of the wind farm is dynamically adjusted to be within the deviation limit, thereby reducing the situation of being assessed and fined due to excessive wind power prediction deviation.

[0022] Additional aspects and advantages of the present invention will be given in part in the following description and in part will be obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] The above and / or additional aspects and advantages of the present invention will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0024] Figure 1 A schematic flow chart of a method for controlling wind power prediction accuracy based on hybrid energy storage on the DC side of a single machine provided by an embodiment of the present invention;

[0025] Figure 2 A schematic diagram of a hybrid energy storage arrangement for a wind farm provided by an embodiment of the present invention;

[0026] Figure 3 A schematic diagram of a deviation between a wind farm predicted power and a wind farm actual total power provided by an embodiment of the present invention;

[0027] Figure 4 A diagram of an execution device for tracking the optimal power of a wind turbine set by adopting an optimal power control strategy at a side end converter of a wind turbine converter of each wind turbine set provided by an embodiment of the present invention;

[0028] Figure 5 A diagram of an execution device for tracking the target power of charging and discharging of an electrochemical energy storage system and a supercapacitor energy storage system provided by an embodiment of the present invention;

[0029] Figure 6A diagram of an execution device for controlling the DC bus voltage through a current loop at a grid-side converter of a wind turbine converter of each wind turbine set provided by an embodiment of the present invention;

[0030] Figure 7 An execution flow chart of a phase-locked loop phase angle calculation module provided by an embodiment of the present invention;

[0031] Figure 8 A schematic flow chart of another method for controlling wind power prediction accuracy based on single-machine DC-side hybrid energy storage provided in an embodiment of the present invention.

[0032] Fig. 9 A schematic structural diagram of a wind power prediction accuracy control device based on single-machine DC-side hybrid energy storage provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0033] Embodiments of the present invention are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present invention, and should not be construed as limiting the present invention.

[0034] It should be noted that the acquisition, storage, use, and processing of data in the technical solution of the present invention are in compliance with the relevant provisions of relevant laws and regulations.

[0035] The following describes, with reference to the accompanying drawings, a method, device, electronic device, and storage medium for controlling wind power prediction accuracy based on single-machine DC-side hybrid energy storage according to an embodiment of the present invention.

[0036] Figure 1 A flow chart of a method for controlling wind power prediction accuracy based on a single-machine DC-side hybrid energy storage system provided by an embodiment of the present invention, wherein: Figure 2As shown, the wind farm includes n wind turbines, and the DC bus side of the wind turbine converter of each wind turbine is connected to the hybrid energy storage, wherein the wind turbine is mainly composed of a power generation system 1 (including an impeller, a rotating chain and a generator), a wind turbine converter 2 and a box transformer 3, and the hybrid energy storage includes an electrochemical energy storage system 4 and a supercapacitor energy storage system 5. The wind turbine converter 2 converts the electric energy generated by the wind turbine into electric energy with the same voltage, frequency and phase as the power grid through AC-DC-AC conversion, including a machine-side converter 2-1, a DC bus 2-2 and a capacitor, and a grid-side converter 2-2. Converter 2-3, grid-connected circuit breaker 2-4, the high-voltage side (35KV) of the box-type transformer 3 is connected to the wind farm collector, and the low-voltage side (690V) is connected to the wind turbine converter 2 and the grid-connected circuit breaker 2-4. The electrochemical energy storage system 4 is composed of a battery system 4-1, a DC-DC bidirectional converter 4-2, and a circuit breaker 4-3. The outlet of the circuit breaker 4-3 is connected to the DC bus 2-2. The supercapacitor energy storage system 5 is composed of a supercapacitor 5-1, a DC-DC bidirectional converter 5-2, and a circuit breaker 5-3. The outlet of the circuit breaker 5-3 is connected to the DC bus 2-2.

[0037] like Figure 1 As shown, the method comprises the following steps:

[0038] Step 101: The total charging and discharging power target value of the hybrid energy storage is converted to Decomposed into the total charging and discharging target power of the electrochemical energy storage system and the total charging and discharging target power of the supercapacitor energy storage system

[0039] In some embodiments, the total charging and discharging power target value of the hybrid energy storage is filtered through a first-order low-pass filter. Decomposed into the total charging and discharging target power of the electrochemical energy storage system and the total charging and discharging target power of the supercapacitor energy storage system Previously, the predicted power of the wind farm and the actual total power of the wind farm within the preset control period of the wind farm were obtained. The predicted power of the wind farm was obtained through the wind power prediction system, and the actual total power of the wind farm was determined by summing the actual power of n wind turbines. The deviation β(j) between the predicted power of the wind farm at time j in the control period and the actual total power of the wind farm is greater than the deviation limit β * In the case of Decomposed into the total charging and discharging target power of the electrochemical energy storage system and the total charging and discharging target power of the supercapacitor energy storage system steps.

[0040] Furthermore, an implementation method for obtaining the predicted power of the wind farm and the actual total power of the wind farm within a preset control period of the wind farm may be to receive the short-term forecast data of the wind farm wind power forecast system the day before, and 15 minutes (the preset control period) may be taken as a forecast point, with a total of 96 forecast points throughout the day, and any short-term forecast data within 15 minutes the day before may be selected as the predicted power of the wind farm; at the same time, the output of the wind farm may be segmented and controlled at intervals of 15 minutes, with a total of 96 control periods throughout the day, and the actual power of each wind turbine in a certain minute or second within the same control period as the forecast point may be obtained as the actual total power of the wind farm.

[0041] In some embodiments, the calculation formula of the deviation β(j) between the predicted power of the wind farm at time j in the control period and the actual total power of the wind farm is formula (1):

[0042]

[0043] Among them, P f (j) is the predicted power of the wind farm at time j in the control period, is the actual power generated by the i-th wind turbine at time j during the control period.

[0044] Furthermore, the deviation β(j) between the predicted power of the wind farm at time j in the control period and the actual total power of the wind farm is greater than the deviation limit β * In the case of hybrid energy storage, the total charging and discharging power target value is The calculation method includes two cases: hybrid energy storage discharge, and the discharge power is positive when β(j)>β * , and hybrid energy storage charging, and when the charging power is negative, β(j)<-β * ; When β(j)>β * Or β(j)<-β * When the total charging and discharging power target value of the hybrid energy storage is The calculation formula is (2)

[0045]

[0046] Specifically, Figure 3 As shown, β * The assessment value is usually 85% when |β(j)|≤β * When the actual power generated by the wind farm is within the deviation limit β * Within this period, the electrochemical energy storage system and the supercapacitor energy storage system do not perform charging and discharging operations; when |β(j)|>β * When the actual power generated by the wind farm exceeds the deviation limit β *The electrochemical energy storage system and the supercapacitor energy storage system perform charging and discharging operations according to the power allocation value. The schematic diagram of the deviation between the predicted power of the wind farm and the actual total power of the wind farm is shown in Figure 3 As shown in the figure, the black curve is the actual total power of the wind farm, and there is a gray prediction box every 15 minutes (the predicted power of the wind farm P f (j) At 0-15 minutes, it is at P f (1)×(1-β * ) to P f (1)×(1+β * ) within 15-30 minutes, it is in P f (2)×(1-β * ) to P f (2)×(1+β * )). When the black curve falls within the gray prediction box, the actual total power generated by the wind farm is within the deviation limit β * When the black curve exceeds the gray prediction box, the actual total power of the wind farm exceeds the deviation limit β * The part beyond the gray prediction box is migrated by the hybrid energy storage through charging and discharging operations.

[0047] In some embodiments, the Decomposed into the total charging and discharging target power of the electrochemical energy storage system and the total charging and discharging target power of the supercapacitor energy storage system One implementation method of may be to use a first-order low-pass filter to Decomposed into low-frequency signal and high-frequency signal, the low-frequency signal corresponds to the total charge and discharge target power of the electrochemical energy storage system The high-frequency signal corresponds to the total charging and discharging target power of the supercapacitor energy storage system in, The calculation method of is as shown in formula (3), The calculation method of is as follows:

[0048]

[0049] Furthermore, a first-order low-pass filter: Among them, s is the Laplace operator, s is a complex number, s=σ+jω, σ is the real part, ω; τ is the time constant.

[0050] For a continuous-time system, after first-order low-pass filtering, the relationship between the output and input is as follows:

[0051]

[0052] Then, z-transform Equation (5) to convert the continuous frequency system into a discrete system. Substituting into equation (5), we get equation (6) and equation (7):

[0053]

[0054] In equations (6) and (7), T is the iteration step, which is also the calculation step. For example, if the data is updated every 1s, T = 1s; R(z) is the input signal at this time step, R(z)z -1 is the input signal of the previous time step, C(z)z -1 is the output signal of the previous time step, and C(z) is the output signal of this time step.

[0055] Therefore, as long as the input signal of the current time step and the previous time step, and the output signal of the previous time step are collected, the signal (low-frequency signal and high-frequency signal) after low-pass filtering in the current time step can be obtained.

[0056] Step 102: according to the state of charge SOC of the electrochemical energy storage system corresponding to each wind turbine group B,i And the state of charge SOC of the supercapacitor energy storage system S,i as well as and Determine the charge and discharge limit coefficient K of each electrochemical energy storage system and supercapacitor energy storage system B,i and K S,i , and according to K B,i and K S,i , calculate the charge and discharge participation factor PF of each electrochemical energy storage system and supercapacitor energy storage system B,i and PF S,i .

[0057] Among them, the state of charge (SOC) B,i or SOC S,i , which represents the ratio of the remaining power of an energy storage device (such as electrochemical energy storage, supercapacitor energy storage) to the rated capacity, usually expressed as a percentage.

[0058] In some embodiments, the state of charge SOC of each collector electrochemical energy storage system is B,i And the state of charge SOC of each collector supercapacitor energy storage system S,i as well as and Determine the charge and discharge limit coefficient K of each collector electrochemical energy storage system and supercapacitor energy storage system B,i and K S,i One implementation method may be to obtain the state of charge SOC of the electrochemical energy storage system corresponding to each wind turbine group. B,i , and SOC B,iCorresponding to the fault state of the wind turbine; in SOC B,i <0.1 or when the corresponding wind turbine fails, the charge and discharge limit coefficient K of the electrochemical energy storage system corresponding to each wind turbine B,i K B_d,i , K B_d,i =0; when 0.1≤SOC B,i <0.2 or the corresponding wind turbine has no fault, K B,i K B_d,i ,K B_d,i =10×(SOC B,i -0.1); in SOC B,i ≥0.2 or when the corresponding wind turbine has no fault, K B,i K B_d,i , K B_d,i =1; in SOC B,i <0.8 or the corresponding wind turbine has no fault, K B,i K B_c,i , K B_c,i =1; at 0.8≤SOC B,i <0.9 or the corresponding wind turbine has no fault, K B,i K B_c,i , K B_c,i =10×(0.9-SOC B,i );In SOC B,i ≥0.9 or when the corresponding wind turbine fails, K B,i K B_c,i , K B_c,i =0; where K B,i The calculation formula is as follows:

[0059]

[0060] K B_d,i for is the positive charge and discharge limit coefficient, K B_c,i for The charge and discharge limit coefficient when it is negative;

[0061] Obtain the state of charge (SOC) of the supercapacitor energy storage system corresponding to each wind turbine S,i , and SOC S,i Corresponding to the fault status of the wind turbine in the wind farm; in SOC S,i <0.1 or when the corresponding wind turbine fails, the charge and discharge limit coefficient K of the energy storage system corresponding to each wind turbine S,i K S_d,i , K S_d,i =0; when 0.1≤SOC S,i <0.2 or the corresponding wind turbine has no fault, KS,i K S_d,i , K S_d,i =10×(SOC S,i -0.1); in SOC S,i ≥0.2 or when the corresponding wind turbine has no fault, K S,i K S_d,i , K B_S,i =1; in SOC S,i <0.8 or the corresponding wind turbine has no fault, K S,i K S_c,i , K S_c,i =1; at 0.8≤SOC S,i <0.9 or the corresponding wind turbine has no fault, K S,i K S_c,i , K S_c,i =10×(0.9-SOC S,i );In SOC S,i ≥0.9 or when the corresponding wind turbine fails, K S,i K S_c,i , K S_c,i =0; where K S,i The calculation formula is as follows:

[0062]

[0063] K S_c,i for is the positive charge and discharge limit coefficient, K S_c,i for The charge and discharge limit coefficient when it is negative.

[0064] In addition, according to K B,i Calculate PF B,i The formulas are as follows (10) and (11):

[0065]

[0066] According to K S,i Calculate PF S,i The formulas are as follows (12) and (13):

[0067]

[0068] Step 103, according to PF B,i and PF S,i , calculate the charge and discharge distribution power P of the electrochemical energy storage system and the supercapacitor energy storage system B,i (j) and P S,i (j) The maximum charging and discharging power of the electrochemical energy storage system and the supercapacitor energy storage system is limited to P B,i (j) and PS,i (j) to obtain the target power of charge and discharge and

[0069] In some embodiments, according to PF B,i Calculate P B ,i(j) is calculated as shown in formula (14), and the maximum charge and discharge power of the electrochemical energy storage system is limited to P B,i (j), we get The formula is as follows (15):

[0070]

[0071]

[0072] In addition, according to PF S,i Calculate P S ,i(j) is calculated as shown in formula (16), and the maximum charging and discharging power of the supercapacitor energy storage system is limited to P S,i (j), we get The formula is as follows (17):

[0073]

[0074] Step 104, by controlling each wind turbine in the wind farm to generate power at the optimal power and controlling the hybrid energy storage tracking device connected to the DC bus side of the n wind turbines and Dynamically control the total actual power generated by the wind farm to be within the deviation limit.

[0075] In some embodiments, the wind turbine converter machine-side converter 2-1 (rectifier) ​​of each wind turbine group adopts an optimal power control strategy to achieve the goal of maximizing wind energy absorption, referring to Figure 4 , Figure 4 The diagram shows an execution device for tracking the optimal power of each wind turbine set by using the optimal power control strategy at the wind turbine converter machine-side converter 2-1. The execution device mainly includes a generator rotor phase calculation module 10 corresponding to the wind turbine set, an optimal power operation control module 11 and a current inner loop control module 12.

[0076] The input of the generator rotor phase calculation module 10 is the generator measured speed ω of the transmission system corresponding to the wind farm g , the output is the generator rotor phase θ g , the calculation formula is as follows:

[0077]

[0078] The optimal power operation control module 11 is composed of an optimal power control torque calculation 11-1 and a q-axis current control target value calculation 11-2. The input of the optimal power control torque calculation 11-1 is the generator measured speed ω g , the output is the generator control target torque T * , the formula is as formula (19):

[0079]

[0080] In formula (19), K opt is the optimal power control torque coefficient, and the q-axis current control target value calculation 11-2 input is the generator control target torque T * , the output is the generator q-axis current control target value The formula is as follows (20):

[0081]

[0082] In formula (20), n p is the number of generator pole pairs, ψ f is the permanent magnet flux of the generator.

[0083] The current inner loop calculation module 12 includes PI calculation (proportional and integral) 12-1 and 12-2, dq coordinate transformation 12-3 and dq coordinate inverse transformation (dq inverse transformation) 12-4. First, the three-phase current measurement value i of the generator is sabc (i sa 、i sb 、i sc ) is converted into dq axis current i through dq transformation sdq (i sd 、i sq ), such as formula (21) and formula (22):

[0084]

[0085] Then, the voltage value corresponding to the current loop is calculated by PI, as shown in formula (23):

[0086]

[0087] Afterwards, by introducing the dq axis cross-influence term (ω e L sq ,ω e L sd ,ω e ψ f ) to obtain the generator stator dq axis voltage control target value, the formula is as follows (24):

[0088]

[0089] In the formula, ω e is the electromagnetic speed of the generator rotor, which is ω e and n p Finally, the generator stator dq axis voltage control target value formula (24) is Substitute the dq coordinate inverse transformation to calculate the modulation voltage control target value of the converter on the machine side of the converter And through sinusoidal pulse width modulation (SPWM) The size and shape of The measured value of the converter DC bus capacitance U is calculated by using 2-1 multiple insulated gate bipolar transistor (IGBT) modules (S1, S2, S3, S4, S5, S6) DC (DC bus voltage), based on U DC Tracking Optimum Power The formulas are as follows (25) and (26):

[0090]

[0091] In other embodiments, the DC side hybrid energy storage device of each wind turbine unit tracks the charging and discharging target power through the DC-DC bidirectional converter 4 / 5-2. refer to Figure 5 , Figure 5 The hybrid energy storage configured for each wind turbine unit corresponding to the wind turbine converter tracks the target power of the electrochemical energy storage system and the supercapacitor energy storage system through a DC-DC bidirectional converter. The execution device mainly includes a charging control process 20 and a discharging control process 21. The charging control process 20 is mainly composed of S1 controlling the conversion switches 20-1 and 20-2, and the charging reference current calculation 20-3. The discharging control process 21 is mainly composed of S2 controlling the conversion switch 21-1, the discharge modulation voltage PI (proportional-integral) calculation 21-2, and the discharge reference current calculation 21-3.

[0092] When the hybrid energy storage (electrochemical energy storage system and supercapacitor energy storage system) is charged, S1 controls the conversion switch to switch to the charging controller, and S2 controls the conversion switch to switch off. The DC-DC bidirectional converter charges the energy storage battery (electrochemical) or supercapacitor through the step-down conversion mode. First, the charging reference current is calculated by the charging reference power, as shown in formula (27):

[0093]

[0094] Then, by substituting the charging reference current and the charging measured current into the PI module (discharge modulation voltage PI calculation 21-2), the charging modulation voltage (pulse width modulation) is calculated as follows (28):

[0095]

[0096] Finally, the IGBT module T1 is controlled to switch on and off at a certain duty cycle by charging modulation voltage, so that the hybrid energy storage can be charged according to the specified reference power (through voltage U ESS The current loop L charges the energy storage battery or super capacitor C1, and the current passing through the resistor L is I L ).

[0097] When the hybrid energy storage is discharged, S1 controls the conversion switch to switch off, and S2 controls the conversion switch to switch to the discharge controller. The DC-DC bidirectional converter discharges the battery or supercapacitor through the boost conversion mode. First, the charging reference current is calculated by the charging reference power, as shown in formula (29):

[0098]

[0099] Then, the discharge reference current and the discharge measured current I L Substitute into the PI module to calculate the discharge modulation voltage, as shown in (30):

[0100]

[0101] Finally, the IGBT module T2 is controlled to switch on and off at a certain duty cycle by the discharge modulation voltage, so that the hybrid energy storage can be discharged according to the specified reference current (through the voltage U DC And switch QF discharges the energy storage battery or super capacitor C2).

[0102] Therefore, the wind turbine converter grid-side converter 2-3 (inverter) of each wind turbine group maintains the DC bus voltage stability through the current loop, thereby transmitting the actual power generated by each wind turbine group in the wind farm to the grid, see Figure 6 , Figure 6 The wind turbine inverter grid-side converter 2-3 mainly includes a phase-locked loop phase angle calculation module 30, a current outer loop calculation module 31 and a current inner loop calculation module 32.

[0103] The phase angle calculation module (phase locked loop) 30 input is the three-phase voltage u measured by the power grid oabc (u oa 、u ob 、u oc ),u oabc Through multiple resistors R, current loop Lf , switch QF, common connection point PCC, current loop L g The output is the grid frequency and phase angle. The execution process of the phase-locked loop phase angle calculation module 30 is shown in Figure 7 First, set the initial phase to θ, substitute it into the dq coordinate transformation, and calculate the grid voltage u od and u oq Value, the formula is as follows (31):

[0104]

[0105] will u oq Substitute into the PI formula to calculate the grid frequency, as shown in formula (32):

[0106]

[0107] Integrate ω to calculate the grid phase angle, as shown in formula (33):

[0108]

[0109] If u oq If it is not close to 0, substitute the calculated grid phase angle into equation (31) to equation (33) to recalculate the grid frequency and grid phase angle until u oq Close to 0, locking the target grid frequency and grid phase angle.

[0110] The current outer loop calculation module 31 includes a d-axis current outer loop PI calculation 31-1 and a q-axis current outer loop PI calculation 31-2. The d-axis current outer loop PI calculation 31-1 inputs the converter DC bus capacitance measurement value U DC and reference value Output is the d-axis current control target value The calculation formula is as follows (34):

[0111]

[0112] The input of the q-axis current outer loop PI calculation 31-2 is the reactive power measurement value Q i and reference value Output is the q-axis current control target value The calculation formula is as follows (35):

[0113]

[0114] The current inner loop calculation module 32 includes PI calculations 32-1 and 32-2, dq coordinate transformation 32-3 and dq coordinate inverse transformation 32-4. First, the inverter output three-phase current measurement value i abc (i a 、ib 、i c ) is converted into dq axis current i through dq transformation dq (i d 、i q ). Then, the voltage value corresponding to the current loop is calculated by PI, as shown in formula (36):

[0115]

[0116] Afterwards, the inverter dq axis voltage control target value is obtained by introducing the dq axis cross-influence term The formula is as follows (37):

[0117]

[0118] Finally, the inverter dq axis voltage control target value Substitute the dq coordinate inverse transformation to calculate the inverter modulation voltage control target value And through sinusoidal pulse width modulation (SPWM) The size and shape of The measured value U of the DC bus capacitance of the converter is controlled by 2-3 IGBT modules (S1, S2, S3, S4, S5, S6) DC (DC bus voltage), The formula is as follows (38):

[0119]

[0120] In the embodiment of the present invention, a method for controlling wind power prediction accuracy based on hybrid energy storage on the DC side of a single machine is provided. The DC bus side of the wind turbine converter of n wind turbines in a wind farm is connected to the hybrid energy storage, the hybrid energy storage includes an electrochemical energy storage system and a supercapacitor energy storage system, the total charge and discharge power target value of the hybrid energy storage and the charge state data of the electrochemical energy storage system and the supercapacitor energy storage system corresponding to the n wind turbines at the current time node are obtained, and the charge and discharge target power of each hybrid energy storage is calculated according to the charge state data; by controlling each wind turbine in the wind farm to generate electricity at the optimal power and controlling the hybrid energy storage connected to the DC bus side corresponding to the n wind turbines to track the charge and discharge target power, the total actual power of the wind farm is dynamically regulated to be within the deviation limit, thereby reducing the situation of being assessed and fined due to excessive wind power prediction deviation.

[0121] In summary, if Figure 8As shown, in the case where the DC bus side of the wind turbine converter of each wind turbine is connected to the hybrid energy storage, the wind power prediction accuracy control method based on the hybrid energy storage on the DC side of the single machine includes: the wind power prediction accuracy control method includes obtaining the wind farm prediction power and the wind farm actual total power within a preset control period of the wind farm, the wind farm prediction power is obtained through the wind power prediction system, and the wind farm actual total power is determined by summing the actual power of n wind turbines; the deviation β(j) between the wind farm prediction power at time j in the control period and the wind farm actual total power is greater than the deviation limit β * Under the condition of Through a first-order low-pass filter Decomposed into the total charging and discharging target power of the electrochemical energy storage system and the total charging and discharging target power of the supercapacitor energy storage system According to the state of charge SOC of the electrochemical energy storage system corresponding to each wind turbine B,i And the state of charge SOC of the supercapacitor energy storage system S,i as well as and Determine the charge and discharge limit coefficient K of each electrochemical energy storage system and supercapacitor energy storage system B,i and K S,i , and according to K B,i and K S,i , calculate the charge and discharge participation factor PF of each electrochemical energy storage system and supercapacitor energy storage system B,i and PF S,i According to PF B,i and PF S,i , calculate the charge and discharge distribution power P of the electrochemical energy storage system and the supercapacitor energy storage system B ,i(j) and P S,i (j) The maximum charging and discharging power of the electrochemical energy storage system and the supercapacitor energy storage system is limited to P B,i (j) and P S,i (j) to obtain the target power of charge and discharge and By controlling each wind turbine in the wind farm to generate power at the optimal power and controlling the hybrid energy storage tracking system connected to the DC bus side of n wind turbines and Dynamically adjust the total actual power of the wind farm within the deviation limit to achieve accurate control of the predicted power of the wind farm.

[0122] In order to implement the above-mentioned embodiment, the present invention further proposes a wind power prediction accuracy control device based on single-machine DC-side hybrid energy storage.

[0123] Fig. 9A structural schematic diagram of a wind power prediction accuracy control device based on a single-machine DC-side hybrid energy storage provided in an embodiment of the present invention, wherein the DC bus side of the wind turbine converters of n wind turbines in a wind farm is incorporated into the hybrid energy storage, and the hybrid energy storage includes an electrochemical energy storage system and a supercapacitor energy storage system.

[0124] like Fig. 9 As shown, the wind power prediction accuracy control device 90 based on single-machine DC side hybrid energy storage includes: a decomposition module 91, a first calculation module 92, a second calculation module 93, and a control module 94.

[0125] Decomposition module 91, used to convert the total charging and discharging power target value of the hybrid energy storage into Decomposed into the total charging and discharging target power of the electrochemical energy storage system and the total charging and discharging target power of the supercapacitor energy storage system

[0126] The first calculation module 92 is used to calculate the state of charge SOC of the electrochemical energy storage system corresponding to each wind turbine group. B,i And the state of charge SOC of the supercapacitor energy storage system S,i as well as and Determine the charge and discharge limit coefficient K of each electrochemical energy storage system and supercapacitor energy storage system B,i and K S,i , and according to the K B,i and K S,i , calculate the charge and discharge participation factor PF of each electrochemical energy storage system and supercapacitor energy storage system B,i and PF S,i ;

[0127] The second calculation module 93 is used to calculate the B,i and PF S,i , calculate the charge and discharge distribution power P of the electrochemical energy storage system and the supercapacitor energy storage system B,i (j) and P S,i (j) The maximum charging and discharging power of the electrochemical energy storage system and the supercapacitor energy storage system is limited to P B,i (j) and P S,i (j) to obtain the target power of charge and discharge and

[0128] The control module 94 is used to control each wind turbine in the wind farm to generate electricity at the optimal power and control the hybrid energy storage tracking system connected to the DC bus side of the n wind turbines. and Dynamically control the total actual power generated by the wind farm to be within the deviation limit.

[0129] Further, in a possible implementation of an embodiment of the present invention, the wind turbine group includes a power generation system 1, a wind turbine converter 2 and a box transformer 3, and the hybrid energy storage includes an electrochemical energy storage system 4 and a supercapacitor energy storage system 5. The wind turbine converter 2 converts the electric energy generated by the wind turbine group into electric energy with the same voltage, frequency and phase as the power grid through AC-DC-AC conversion, including a machine-side converter 2-1, a DC bus 2-2 and a capacitor, a network-side converter 2-3, and a grid-connected circuit breaker. The high-voltage side of the box-type transformer 3 is connected to the wind farm collector, and the low-voltage side is connected to the wind turbine converter 2 and the grid-connected circuit breaker 2-4. The electrochemical energy storage system 4 is composed of a battery system 4-1, a DC-DC bidirectional converter 4-2, and a circuit breaker 4-3. The outlet of the circuit breaker 4-3 is connected to the DC bus 2-2. The supercapacitor energy storage system 5 is composed of a supercapacitor 5-1, a DC-DC bidirectional converter 5-2, and a circuit breaker 5-3. The outlet of the circuit breaker 5-3 is connected to the DC bus 2-2.

[0130] Furthermore, in a possible implementation of the embodiment of the present invention, the device further includes:

[0131] An acquisition module is used to acquire the predicted power of the wind farm and the actual total power of the wind farm within a preset control period of the wind farm. The predicted power of the wind farm is obtained through a wind power prediction system, and the actual total power of the wind farm is determined by summing the actual power of n wind turbines.

[0132] The judgment module is used to determine whether the deviation β(j) between the predicted power of the wind farm at time j in the control period and the actual total power of the wind farm is greater than the deviation limit β * In the case of Decomposed into the total charging and discharging target power of the electrochemical energy storage system and the total charging and discharging target power of the supercapacitor energy storage system steps.

[0133] Further, in a possible implementation of the embodiment of the present invention, the calculation formula of the deviation β(j) between the predicted power of the wind farm at time j in the control period and the actual total power of the wind farm is:

[0134]

[0135] Among them, P f (j) is the predicted power of the wind farm at time j in the control period, is the actual power generated by the i-th wind turbine at time j during the control period.

[0136] Furthermore, in a possible implementation of the embodiment of the present invention, the total charging and discharging power target value of the hybrid energy storage is The calculation methods include:

[0137] The deviation β(j) between the predicted power of the wind farm at time j in the control period and the actual total power of the wind farm is greater than the deviation limit β * There are two cases: hybrid energy storage discharge, and the discharge power is positive when β(j)>β * , and hybrid energy storage charging, and when the charging power is negative, β(j)<-β * ;

[0138] When β(j)>β * Or β(j)<-β * When the total charging and discharging power target value of the hybrid energy storage is The calculation formula is

[0139]

[0140] Further, in a possible implementation of the embodiment of the present invention, the first calculation module 92 is specifically configured to:

[0141] Obtain the state of charge (SOC) of the electrochemical energy storage system corresponding to each wind turbine B,i , and SOC B,i Corresponding to the fault status of the wind turbine;

[0142] In SOC B,i <0.1 or when the corresponding wind turbine fails, the charge and discharge limit coefficient K of the electrochemical energy storage system corresponding to each wind turbine B,i K B_d,i , K B_d,i =0; when 0.1≤SOC B,i <0.2 or the corresponding wind turbine has no fault, K B,i K B_d,i ,K B_d,i =10×(SOC B,i -0.1); in SOC B,i ≥0.2 or when the corresponding wind turbine has no fault, K B,i K B_d,i , K B_d,i =1; in SOC B,i <0.8 or the corresponding wind turbine has no fault, K B,i K B_c,i , K B_c,i =1; at 0.8≤SOC B,i <0.9 or the corresponding wind turbine has no fault, K B,i K B_c,i , K B_c,i =10×(0.9-SOC B,i);In SOC B,i ≥0.9 or when the corresponding wind turbine fails, K B,i K B_c,i , K B_c,i =0; where

[0143]

[0144] for is the positive charge and discharge limit coefficient, K B_c,i for The charge and discharge limit coefficient when it is negative;

[0145] Obtain the state of charge (SOC) of the supercapacitor energy storage system corresponding to each wind turbine S,i , and SOC S,i The fault status of the wind turbines in the corresponding wind farm;

[0146] In SOC S,i <0.1 or when the corresponding wind turbine fails, the charge and discharge limit coefficient K of the supercapacitor energy storage system corresponding to each wind turbine S,i K S_d,i , K S_d,i =0; when 0.1≤SOC S,i <0.2 or the corresponding wind turbine has no fault, K S,i K S_d,i , K S_d,i =10×(SOC S,i -0.1); in SOC S,i ≥0.2 or when the corresponding wind turbine has no fault, K S,i K S_d,i , K B_S,i =1; in SOC S,i <0.8 or the corresponding wind turbine has no fault, K S,i K S_c,i , K S_c,i =1; at 0.8≤SOC S,i <0.9 or the corresponding wind turbine has no fault, K S,i K S_c,i , K S_c,i =10×(0.9-SOC S,i );In SOC S,i ≥0.9 or when the corresponding wind turbine fails, K S,i K S_c,i , K S_c,i =0; where

[0147]

[0148] K S_c,i for is the positive charge and discharge limit coefficient, K S_c,i for The charge and discharge limit coefficient when it is negative.

[0149] It should be noted that the above explanation of the method embodiment is also applicable to the device of this embodiment, and will not be repeated here.

[0150] In the embodiment of the present invention, a method for controlling wind power prediction accuracy based on hybrid energy storage on the DC side of a single machine is provided. The DC bus side of the wind turbine converter of n wind turbines in a wind farm is connected to the hybrid energy storage, the hybrid energy storage includes an electrochemical energy storage system and a supercapacitor energy storage system, the total charge and discharge power target value of the hybrid energy storage and the charge state data of the electrochemical energy storage system and the supercapacitor energy storage system corresponding to the n wind turbines at the current time node are obtained, and the charge and discharge target power of each hybrid energy storage is calculated according to the charge state data; by controlling each wind turbine in the wind farm to generate electricity at the optimal power and controlling the hybrid energy storage connected to the DC bus side corresponding to the n wind turbines to track the charge and discharge target power, the total actual power of the wind farm is dynamically regulated to be within the deviation limit, thereby reducing the situation of being assessed and fined due to excessive wind power prediction deviation.

[0151] In order to implement the above embodiment, the present invention further provides an electronic device, including:

[0152] at least one processor; and

[0153] a memory communicatively connected to the at least one processor; wherein,

[0154] The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can perform the aforementioned method.

[0155] In order to implement the above embodiment, the present invention further proposes a non-transitory computer-readable storage medium storing computer instructions, where the computer instructions are used to enable the computer to execute the above method.

[0156] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0157] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In the description of the present invention, the meaning of "plurality" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0158] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, segment or portion of code comprising one or more executable instructions for implementing the steps of a custom logical function or process, and the scope of the preferred embodiments of the present invention includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in reverse order depending on the functions involved, which should be understood by technicians in the technical field to which the embodiments of the present invention belong.

[0159] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute the instructions), or in combination with these instruction execution systems, devices or apparatuses. For the purpose of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in combination with these instruction execution systems, devices or apparatuses. More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk box (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium and then editing, interpreting or processing in other suitable ways if necessary, and then stored in a computer memory.

[0160] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0161] A person skilled in the art may understand that all or part of the steps in the method for implementing the above-mentioned embodiment may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiment.

[0162] In addition, each functional unit in each embodiment of the present invention may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of software functional modules. If the integrated module is implemented in the form of software functional modules and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0163] The storage medium mentioned above may be a read-only memory, a magnetic disk or an optical disk, etc. Although the embodiments of the present invention have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limiting the present invention. A person of ordinary skill in the art may change, modify, replace and modify the above embodiments within the scope of the present invention.

Claims

1. A wind power prediction accuracy control method based on single-machine DC side hybrid energy storage, characterized in that: The DC bus side of the wind turbine converter of n wind turbines in the wind farm is connected to a hybrid energy storage system, the hybrid energy storage system includes an electrochemical energy storage system and a supercapacitor energy storage system, and the method includes: The total charging and discharging power target value of the hybrid energy storage is converted to Decomposed into the total charging and discharging target power of the electrochemical energy storage system and the total charging and discharging target power of the supercapacitor energy storage system According to the state of charge SOC of the electrochemical energy storage system corresponding to each wind turbine B,i And the state of charge SOC of the supercapacitor energy storage system S,i as well as and Determine the charge and discharge limit coefficient K of each electrochemical energy storage system and supercapacitor energy storage system B,i and K S,i , and according to the K B,i and K S,i , calculate the charge and discharge participation factor PF of each electrochemical energy storage system and supercapacitor energy storage system B,i and PF S,i ; According to the PF B,i and PF S,i , calculate the charge and discharge distribution power P of the electrochemical energy storage system and the supercapacitor energy storage system B,i (j) and P S,i (j) The maximum charging and discharging power of the electrochemical energy storage system and the supercapacitor energy storage system is limited to P B,i (j) and P S,i (j) to obtain the target power of charge and discharge and By controlling each wind turbine in the wind farm to generate power at the optimal power and controlling the hybrid energy storage tracking system connected to the DC bus side of n wind turbines and Dynamically control the total actual power generated by the wind farm to be within the deviation limit.

2. The method according to claim 1, characterized in that in, The wind turbine set includes a power generation system 1, a wind turbine converter 2 and a box-type transformer 3. The hybrid energy storage includes an electrochemical energy storage system 4 and a supercapacitor energy storage system 5. The wind turbine converter 2 converts the electric energy generated by the wind turbine set into electric energy with the same voltage, frequency and phase as the power grid through AC-DC-AC conversion, including a machine-side converter 2-1, a DC bus 2-2 and capacitors, a grid-side converter 2-3, and a grid-connected circuit breaker 2-4. The high-voltage side of the box-type transformer 3 is connected to the wind farm collector, and the low-voltage side is connected to the wind turbine converter 2 and the grid-connected circuit breaker 2-4. The electrochemical energy storage system 4 is composed of a battery system 4-1, a DC-DC bidirectional converter 4-2, and a circuit breaker 4-3. The outlet of the circuit breaker 4-3 is connected to the DC bus 2-2. The supercapacitor energy storage system 5 is composed of a supercapacitor 5-1, a DC-DC bidirectional converter 5-2, and a circuit breaker 5-3. The outlet of the circuit breaker 5-3 is connected to the DC bus 2-2.

3. The method according to claim 1, characterized in that The method further comprises: Obtain the predicted power of the wind farm and the actual total power of the wind farm within the preset control period of the wind farm. The predicted power of the wind farm is obtained through the wind power prediction system, and the actual total power of the wind farm is determined by summing the actual power of n wind turbines; The deviation β(j) between the predicted power of the wind farm at time j in the control period and the actual total power of the wind farm is greater than the deviation limit β * In the case of Decomposed into the total charging and discharging target power of the electrochemical energy storage system and the total charging and discharging target power of the supercapacitor energy storage system steps.

4. The method according to claim 3, characterized in that The calculation formula of the deviation β(j) between the predicted power of the wind farm at time j in the control period and the actual total power of the wind farm is: Among them, P f (j) is the predicted power of the wind farm at time j in the control period, is the actual power generated by the i-th wind turbine at time j during the control period.

5. The method according to claim 4, characterized in that The total charging and discharging power target value of the hybrid energy storage The calculation methods include: The deviation β(j) between the predicted power of the wind farm at time j in the control period and the actual total power of the wind farm is greater than the deviation limit β * There are two cases: hybrid energy storage discharge, and the discharge power is positive when β(j)>β * , and hybrid energy storage charging, and when the charging power is negative, β(j)<-β * ; When β(j)>β * Or β(j)<-β * When the total charging and discharging power target value of the hybrid energy storage is The calculation formula is 6. The method according to claim 1, characterized in that According to the state of charge SOC of the electrochemical energy storage system corresponding to each wind turbine group B,i And the state of charge SOC of the supercapacitor energy storage system S,i as well as and Determine the charge and discharge limit coefficient K of each electrochemical energy storage system and supercapacitor energy storage system B,i and K S,i ,include: Obtain the state of charge (SOC) of the electrochemical energy storage system corresponding to each wind turbine B,i , and SOC B,i Corresponding to the fault status of the wind turbine; In SOC B,i <0.1 or when the corresponding wind turbine fails, the charge and discharge limit coefficient K of the electrochemical energy storage system corresponding to each wind turbine B,i K B_d,i , K B_d,i =0; when 0.1≤SOC B,i <0.2 or the corresponding wind turbine has no fault, K B,i K B_d,i ,K B_d,i =10×(SOC B,i -0.1); in SOC B,i ≥0.2 or when the corresponding wind turbine has no fault, K B,i K B_d,i , K B_d,i =1; in SOC B,i <0.8 or the corresponding wind turbine has no fault, K B,i K B_c,i , K B_c,i =1; at 0.8≤SOC B,i <0.9 or the corresponding wind turbine has no fault, K B,i K B_c,i , K B_c,i =10×(0.9-SOC B,i );In SOC B,i ≥0.9 or when the corresponding wind turbine fails, K B,i K B_c,i , K B_c,i =0; where K B_d,i for is the positive charge and discharge limit coefficient, K B_c,i for The charge and discharge limit coefficient when it is negative; Obtain the state of charge (SOC) of the supercapacitor energy storage system corresponding to each wind turbine S,i , and SOC S,i The fault status of the wind turbines in the corresponding wind farm; In SOC S,i <0.1 or when the corresponding wind turbine fails, the charge and discharge limit coefficient K of the supercapacitor energy storage system corresponding to each wind turbine S,i K S_d,i , K S_d,i =0; when 0.1≤SOC S,i <0.2 or the corresponding wind turbine has no fault, K S,i K S_d,i , K S_d,i =10×(SOC S,i -0.1); in SOC S,i ≥0.2 or when the corresponding wind turbine has no fault, K S,i K S_d,i , K B_S,i =1; in SOC S,i <0.8 or the corresponding wind turbine has no fault, K S,i K S_c,i , K S_c,i =1; at 0.8≤SOC S,i <0.9 or the corresponding wind turbine has no fault, K S,i K S_c,i , K S_c,i =10×(0.9-SOC S,i );In SOC S,i ≥0.9 or when the corresponding wind turbine fails, K S,i K S_c,i , K S_c,i =0; where K S_c,i for is the positive charge and discharge limit coefficient, K S_c,i for The charge and discharge limit coefficient when it is negative.

7. A wind power prediction accuracy control device based on a single-machine DC-side hybrid energy storage, characterized in that: The DC bus side of the wind turbine converter of n wind turbines in the wind farm is connected to a hybrid energy storage system, the hybrid energy storage system includes an electrochemical energy storage system and a supercapacitor energy storage system, and the device includes: The decomposition module is used to convert the total charging and discharging power target value of the hybrid energy storage into Decomposed into the total charging and discharging target power of the electrochemical energy storage system and the total charging and discharging target power of the supercapacitor energy storage system The first calculation module is used to calculate the state of charge SOC of the electrochemical energy storage system corresponding to each wind turbine group. B,i And the state of charge SOC of the supercapacitor energy storage system S,i as well as and Determine the charge and discharge limit coefficient K of each electrochemical energy storage system and supercapacitor energy storage system B,i and K S,i , and according to the K B,i and K S,i , calculate the charge and discharge participation factor PF of each electrochemical energy storage system and supercapacitor energy storage system B,i and PF S,i ; The second calculation module is used to calculate the B,i and PF S,i , calculate the charge and discharge distribution power P of the electrochemical energy storage system and the supercapacitor energy storage system B,i (j) and P S,i (j) The maximum charging and discharging power of the electrochemical energy storage system and the supercapacitor energy storage system is limited to P B,i (j) and P S,i (j) to obtain the charge and discharge target power P B * ,i(j) and The control module is used to control the wind turbines in the wind farm to generate electricity at the optimal power and control the hybrid energy storage tracking system connected to the DC bus side of the n wind turbines. and Dynamically control the total actual power generated by the wind farm to be within the deviation limit.

8. The device according to claim 7, characterized in that in, The wind turbine set includes a power generation system 1, a wind turbine converter 2 and a box-type transformer 3. The hybrid energy storage includes an electrochemical energy storage system 4 and a supercapacitor energy storage system 5. The wind turbine converter 2 converts the electric energy generated by the wind turbine set into electric energy with the same voltage, frequency and phase as the power grid through AC-DC-AC conversion, including a machine-side converter 2-1, a DC bus 2-2 and capacitors, a grid-side converter 2-3, and a grid-connected circuit breaker 2-4. The high-voltage side of the box-type transformer 3 is connected to the wind farm collector, and the low-voltage side is connected to the wind turbine converter 2 and the grid-connected circuit breaker 2-4. The electrochemical energy storage system 4 is composed of a battery system 4-1, a DC-DC bidirectional converter 4-2, and a circuit breaker 4-3. The outlet of the circuit breaker 4-3 is connected to the DC bus 2-2. The supercapacitor energy storage system 5 is composed of a supercapacitor 5-1, a DC-DC bidirectional converter 5-2, and a circuit breaker 5-3. The outlet of the circuit breaker 5-3 is connected to the DC bus 2-2.

9. The device according to claim 7, characterized in that The device also includes: An acquisition module is used to acquire the predicted power of the wind farm and the actual total power of the wind farm within a preset control period of the wind farm. The predicted power of the wind farm is obtained through a wind power prediction system, and the actual total power of the wind farm is determined by summing the actual power of n wind turbines. The judgment module is used to determine whether the deviation β(j) between the predicted power of the wind farm at time j in the control period and the actual total power of the wind farm is greater than the deviation limit β * In the case of Decomposed into the total charging and discharging target power of the electrochemical energy storage system and the total charging and discharging target power of the supercapacitor energy storage system steps.

10. The device according to claim 9, characterized in that The calculation formula of the deviation β(j) between the predicted power of the wind farm at time j in the control period and the actual total power of the wind farm is: Among them, P f (j) is the predicted power of the wind farm at time j in the control period, is the actual power generated by the i-th wind turbine at time j during the control period.

11. The device according to claim 10, characterized in that The total charging and discharging power target value of the hybrid energy storage The calculation methods include: The deviation β(j) between the predicted power of the wind farm at time j in the control period and the actual total power of the wind farm is greater than the deviation limit β * There are two cases: hybrid energy storage discharge, and the discharge power is positive when β(j)>β * , and hybrid energy storage charging, and when the charging power is negative, β(j)<-β * ; When β(j)>β * Or β(j)<-β * When the total charging and discharging power target value of the hybrid energy storage is The calculation formula is 12. The device according to claim 7, characterized in that The first calculation module is specifically used for: Obtain the state of charge (SOC) of the electrochemical energy storage system corresponding to each wind turbine B,i , and SOC B,i Corresponding to the fault status of the wind turbine; In SOC B,i <0.1 or when the corresponding wind turbine fails, the charge and discharge limit coefficient K of the electrochemical energy storage system corresponding to each wind turbine B,i K B_d,i , K B_d,i =0; when 0.1≤SOC B,i <0.2 or the corresponding wind turbine has no fault, K B,i K B_d,i ,K B_d,i =10×(SOC B,i -0.1); in SOC B,i ≥0.2 or when the corresponding wind turbine has no fault, K B,i K B_d,i , K B_d,i =1; in SOC B,i <0.8 or the corresponding wind turbine has no fault, K B,i K B_c,i , K B_c,i =1; at 0.8≤SOC B,i <0.9 or the corresponding wind turbine has no fault, K B,i K B_c,i , K B_c,i =10×(0.9-SOC B,i );In SOC B,i ≥0.9 or when the corresponding wind turbine fails, K B,i K B_c,i , K B_c,i =0; where K B_d,i for is the positive charge and discharge limit coefficient, K B_c,i for The charge and discharge limit coefficient when it is negative; Obtain the state of charge (SOC) of the supercapacitor energy storage system corresponding to each wind turbine S,i , and SOC S,i The fault status of the wind turbines in the corresponding wind farm; In SOC S,i <0.1 or when the corresponding wind turbine fails, the charge and discharge limit coefficient K of the supercapacitor energy storage system corresponding to each wind turbine S,i K S_d,i , K S_d,i =0; when 0.1≤SOC S,i <0.2 or the corresponding wind turbine has no fault, K S,i K S_d,i , K S_d,i =10×(SOC S,i -0.1); in SOC S,i ≥0.2 or when the corresponding wind turbine has no fault, K S,i K S_d,i , K B_S,i =1; in SOC S,i <0.8 or the corresponding wind turbine has no fault, K S,i K S_c,i , K S_c,i =1; at 0.8≤SOC S,i <0.9 or the corresponding wind turbine has no fault, K S,i K S_c,i , K S_c,i =10×(0.9-SOC S,i );In SOC S,i ≥0.9 or when the corresponding wind turbine fails, K S,i K S_c,i , K S_c,i =0; where K S_c,i for is the positive charge and discharge limit coefficient, K S_c,i for The charge and discharge limit coefficient when it is negative.

13. An electronic device, characterized in that: include: at least one processor; as well as a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method according to any one of claims 1 to 6.

14. A non-transitory computer-readable storage medium storing computer instructions, characterized in that: The computer instructions are used to cause the computer to execute the method according to any one of claims 1-6.

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