Energy storage capacity quantification and evaluation method considering frequency support requirements and low voltage ride through

Abstract

The present invention discloses a method for quantitatively evaluating energy storage capacity that considers frequency support requirements and low-voltage ride-through. The method includes the following steps: constructing a wind turbine grid-connected system with virtual inertia damping control and low-voltage ride-through control; analyzing the active power variation characteristics and system frequency dynamics when the wind turbine grid-connected voltage drops to different degrees; quantitatively analyzing the system frequency dynamics after adding virtual inertia damping control; configuring control parameters based on frequency response indicators; and quantitatively analyzing the energy storage capacity required for the wind power transmission system, taking into account low-voltage ride-through and system frequency limitations. By considering frequency support requirements and low-voltage ride-through control, the present invention can more comprehensively evaluate energy storage capacity, thereby providing guidance for energy storage capacity configuration in engineering projects.

Description

Technical Field

[0001] The present invention relates to the field of assessment, and in particular to a method for quantitatively assessing energy storage capacity taking into account frequency support requirements and low voltage ride-through. Background Art

[0002] To achieve sustainable energy development, renewable energy sources such as wind power are booming. Currently, wind power accounts for an increasing proportion of power. However, the converter control system of wind turbines makes them virtually unresponsive to changes in system frequency, thereby weakening the system's inertia and damping, significantly reducing the system's frequency stability. Therefore, in power systems with a high proportion of renewable energy, energy storage technology has emerged. Leveraging the complementary characteristics of battery energy storage systems and wind power generation, it can improve system operating characteristics while meeting frequency response requirements.

[0003] To enable energy storage converters to provide inertia response support and primary frequency regulation for the power grid, scholars have proposed a variety of energy storage converter control strategies. Among them, some scholars have proposed a virtual inertia control strategy for energy storage converters based on the frequency differential principle using a frequency-locked loop and an extended observer to improve the inertia response capability of the energy storage converter. Others have introduced virtual inertia control and droop control into the energy storage converter to simulate the inertia response and primary frequency regulation of synchronous machines. Others have introduced virtual synchronous machine (VSG) control and proposed a fuzzy adaptive VSG control that takes into account energy storage capacity and SOC constraints. Therefore, determining the capacity of the energy storage system is the basis for using energy storage to improve the frequency response capability of wind turbines.

[0004] To quantitatively assess energy storage capacity, some researchers have used the inertia time constant and primary frequency modulation coefficient in energy storage control to quantitatively analyze the impact of energy storage on the power system and, in combination with frequency response indicators, to determine the energy storage scale. Other researchers, in order to ensure that energy storage has a frequency response similar to that of synchronous generators, have determined the rated power and capacity of energy storage by analogy with the energy change characteristics of synchronous generator rotors when the frequency changes. Some researchers have considered wind power fluctuations and determined the minimum energy storage capacity based on system frequency deviation indicators. However, existing energy storage capacity assessment research has mostly focused on disturbances such as wind speed fluctuations and sudden load changes, while research on energy storage capacity assessment based on short-circuit faults is relatively limited. Furthermore, the low-voltage ride-through control issues of energy storage systems caused by short-circuit faults may affect energy storage capacity requirements. Therefore, further research is needed to develop a method for quantifying energy storage capacity that comprehensively considers frequency support requirements and low-voltage ride-through control. Summary of the Invention

[0005] The purpose of the present invention is to provide a method for quantitatively evaluating energy storage capacity taking into account frequency support requirements and low voltage ride-through. The method conducts quantitative evaluation research on energy storage capacity based on short-circuit faults. This method can more accurately and comprehensively evaluate the size of energy storage capacity.

[0006] To achieve the above object, the present invention provides the following solutions:

[0007] A quantitative evaluation method for energy storage capacity considering frequency support requirements and low voltage ride-through is characterized by including the following steps:

[0008] Step 100: Construct a wind turbine grid-connected system including virtual inertia damping control and low-pressure ride-through control;

[0009] Step 200: Analyze the active power variation characteristics and system frequency dynamic characteristics when the wind turbine grid-connected voltage drops to different degrees;

[0010] Step 300: Quantitatively analyzing the frequency dynamic characteristics of the system after adding virtual inertia damping control;

[0011] Step 400: configuring control parameters according to frequency response indicators;

[0012] Step 500: Considering low voltage ride-through and system frequency limitations, quantitatively analyze the energy storage capacity required for the wind power transmission system;

[0013] According to the specific embodiments provided by the present invention, the present invention discloses the following technical effects:

[0014] This paper proposes a quantitative energy storage capacity assessment method that considers frequency support requirements and low-voltage ride-through, comprehensively addressing the issue of quantitative energy storage capacity assessment under short-circuit fault conditions. Based on a quantitative analysis of the frequency variation characteristics before and after the addition of energy storage under short-circuit conditions, and taking into account the impact of the energy storage system's low-voltage ride-through control on the storage system's output active power, this method comprehensively considers both frequency support requirements and low-voltage ride-through, enabling a comprehensive and accurate assessment of energy storage capacity. The theoretical analysis was then validated through time-domain simulation. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0016] Figure 1 A flowchart of a method for quantitatively evaluating energy storage capacity considering frequency support requirements and low voltage ride-through provided in an embodiment of the present invention;

[0017] Figure 2 This is a block diagram of virtual inertial damping control using energy storage in an embodiment of the present invention;

[0018] Figure 3This is a curve diagram of the change of the active power of the wind turbine taking into account the low voltage ride-through control in an embodiment of the present invention;

[0019] Figure 4 Schematic diagram of an equivalent simulation system according to an embodiment of the present invention;

[0020] Figure 5 A comparison diagram of the system frequency simulation curve and the theoretical curve in an embodiment of the present invention;

[0021] Figure 6 This is a comparison diagram of system frequency curves before and after adding energy storage in an embodiment of the present invention;

[0022] Figure 7 (a) is a curve showing the angular frequency change of the wind turbine grid connection point when the wind turbine grid connection voltage drops to 0.9 pu in an embodiment of the present invention;

[0023] Figure 7 (b) is a curve showing the angular frequency change of the wind turbine grid connection point when the wind turbine grid connection voltage drops to 0.8 pu in an embodiment of the present invention;

[0024] Figure 8 (a) is a comparison of the angular frequency change curves of the wind turbine grid connection point before and after adding energy storage when the wind turbine grid connection voltage drops to 0.7 pu in an embodiment of the present invention;

[0025] Figure 8 (b) is the required energy storage output active power change curve when the wind turbine grid-connected voltage drops to 0.7 pu in an embodiment of the present invention;

[0026] Figure 9 (a) is a comparison of the angular frequency change curves of the wind turbine grid connection point before and after adding energy storage when the wind turbine grid connection voltage drops to 0.5 pu in an embodiment of the present invention;

[0027] Figure 9 (b) is the curve showing the change in active power output of the energy storage required when the grid-connected voltage of the wind turbine drops to 0.5 pu in an embodiment of the present invention. DETAILED DESCRIPTION

[0028] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0029] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0030] Figure 1 Flowchart of the method for quantitatively evaluating energy storage capacity considering frequency support requirements and low voltage ride-through in an embodiment of the present invention. Figure 1 As shown, the following steps are included:

[0031] Step 100: Construct a wind turbine grid-connected system with virtual inertia damping control and low-voltage ride-through control, specifically including:

[0032] The direct-drive wind turbine model mainly includes the direct-drive permanent magnet generator, the generator-side converter, the grid-side converter, and their control systems. The energy storage system model includes the energy storage battery, the converter, and its control equipment.

[0033] The virtual inertia damping control block diagram is as follows: Figure 2 As shown in the figure, to ensure that the wind turbine has the same inertia damping characteristics, the energy storage system is used to provide active power support for the wind turbine. The differential component of the system frequency is introduced to provide inertia support for the wind turbine, and the proportional component of the frequency is introduced to provide damping support for the wind turbine. The system frequency is the angular frequency of the wind turbine's grid connection point. The virtual inertia damping control strategy equation is shown below:

[0034]

[0035] Among them, P ESS1 、P ESS2 are the inertia response support power and primary frequency modulation support power provided by the energy storage device respectively; H vir 、D vir are the virtual inertia control coefficient and the virtual damping control coefficient respectively; Δf is the change of system frequency; P ESSref It is the active power reference value of the energy storage inverter.

[0036] Step 200: Analyze the active power variation characteristics and system frequency dynamic characteristics when the wind turbine grid-connected voltage drops to different degrees, specifically including:

[0037] When the voltage at the wind turbine grid connection point drops below 0.9pu, the wind turbine's low voltage ride-through control takes effect. At this time, the wind turbine outputs reactive power to improve grid voltage stability. At the same time, the wind turbine's grid-connected active power drops, causing dynamic changes in system frequency. During a short-circuit fault, the wind turbine's active power and the wind turbine's grid-connected voltage satisfy the following relationship:

[0038]

[0039] Among them, P w is the active power output of the fan, k iq is the wind turbine reactive current regulation coefficient, k i is a constant, usually taken as 1.05, u gpu is the wind turbine grid-connected voltage during a short-circuit fault.

[0040] The change curve of the wind turbine active power considering the low voltage ride through control is as follows Figure 3 As shown, the active power of the fan in steady state is P sw , after a short circuit occurs at time t0, the wind turbine enters the low penetration zone, at which time the wind turbine active power drops to P w . t p When the short-circuit fault is cleared, the active power of the wind turbine returns to the steady-state value at a certain rate of change, which is the recovery zone.

[0041] The change in system active power during the short-circuit fault ΔP s for:

[0042]

[0043] Where ΔP G is the active power change of the synchronous machine during the short-circuit fault, P sw is the rated active power of the fan, P wi is the active power output by the i-th wind turbine during the short-circuit fault, and m is the number of wind turbines.

[0044] The time domain expression of the system frequency change curve when the system inertia damping takes effect during the short-circuit fault is:

[0045]

[0046] Where f0 is the rated frequency of the system, H s 、D s are the system inertia time constant and system damping parameter respectively, and t0 is the fault start time.

[0047] During the inertia response phase, the system frequency continues to rise until the fault is cleared. After the fault is cleared, the synchronous machine's electromagnetic power recovers rapidly, and the wind turbine's active power also recovers at a certain rate. When the system's active power difference is zero, according to Equation (4), the frequency change rate is zero at this time, and the frequency reaches its peak. Therefore, if the wind turbine's active power recovery time is ignored, the frequency corresponding to the moment of fault clearance is the maximum system frequency.

[0048] Step 300: Quantitatively analyzing the system frequency dynamic characteristics after adding virtual inertia damping control, specifically including:

[0049] When virtual inertia and virtual damping control take effect during a short-circuit fault, the energy storage output active power P ESS Satisfy the following formula.

[0050]

[0051] Among them, fpll Measured frequency for the phase-locked loop.

[0052] The frequency measured by the phase-locked loop is equal to the system frequency, that is, it is assumed that the phase-locked loop can accurately measure the real-time system frequency change.

[0053] The system frequency dynamics after adding virtual inertia damping control are derived from the system frequency variation curve without energy storage and the relationship between energy storage output active power, virtual inertia, and virtual damping parameters. After adding energy storage, the system frequency variation curve during a fault period satisfies the following equation.

[0054]

[0055] By taking the derivative of the above formula, we can get the initial frequency change rate after adding energy storage:

[0056]

[0057] Through the above analysis, it can be found that after adding energy storage, the equivalent inertia time constant H of the system is s1 and the equivalent damping parameter H D1 Increase, that is:

[0058]

[0059] After adding energy storage, the equivalent inertia time constant and equivalent damping parameter of the system increase. Therefore, adding the energy storage system can enable the wind turbine to participate in the inertia response regulation of the system frequency.

[0060] Step 400: Configuring control parameters according to frequency response indicators, specifically including:

[0061] Determine the system frequency response index, which includes the system frequency maximum and the initial frequency change rate. Due to the low inertia and low damping characteristics of wind turbines, a high wind power penetration grid will deteriorate the system frequency stability and may even cause wind turbines to be disconnected from the grid due to excessive frequency deviation. Therefore, according to the wind turbine grid connection guidelines, the maximum frequency deviation Δf max0 Set to 1.5Hz, and the initial rate of change of system frequency ROCOF is set to 0.5Hz / s.

[0062] The control parameters include a virtual inertia parameter and a virtual damping parameter.

[0063] According to the frequency response index, the virtual inertia parameter and the virtual damping parameter are adjusted so that the maximum frequency and the initial frequency change rate meet the frequency index requirements, thereby determining the minimum values of the virtual inertia parameter and the virtual damping parameter.

[0064]

[0065] Step 500: Considering low voltage ride-through and system frequency limitations, quantitatively analyze the energy storage capacity required for the wind power transmission system, specifically including:

[0066] The active power output of the energy storage is determined based on the relationship between the active power output of the energy storage, the virtual inertia damping parameters, and the system frequency. When the system frequency variation curve and the virtual inertia and virtual damping parameters are known, and the effects of wind speed fluctuations are ignored, the required energy storage capacity (per unit value) can be calculated:

[0067]

[0068] Considering the energy storage system's low voltage ride-through control, calculate the active power output by the energy storage when the grid-connected voltage drops to different levels, and update the energy storage capacity assessment value. The energy storage's low voltage ride-through control will prevent the energy storage from outputting its rated power. Therefore, when a short circuit occurs in the system, the required energy storage capacity assessment must take into account not only the system frequency limit but also the energy storage's low voltage ride-through control. Taking into account the energy storage system's low voltage ride-through control, the energy storage output active power (per unit) during the short circuit fault can be calculated as:

[0069]

[0070] Among them, u Epu is the per-unit value of the energy storage grid-connected voltage, k ie is the reactive current regulation coefficient of energy storage, k is a constant, usually taken as 1.0, P EN is the rated value (per unit) of the energy storage output active power, which is taken as 1 here.

[0071] Therefore, considering the low voltage ride-through of the energy storage system, the energy storage capacity P is considered, considering the frequency support demand and low voltage ride-through control. ESS :

[0072]

[0073] Therefore, when considering low-voltage ride-through control, the energy storage capacity required by the system will gradually increase, and may even exceed the current energy storage configuration index.

[0074] The present invention adopts Example 1 to verify the effect of this method:

[0075] Figure 4 This is a structural diagram of a single-machine system with wind storage according to Example 1 of the present invention, wherein the wind turbine power is 2 pu; the synchronous machine power is 1 pu; the load power is 3 pu; the inertia time constant of the synchronous machine is 1, the damping parameter is 1, the phase-locked loop differential parameter is 20, and the phase-locked loop proportional parameter is 50.

[0076] In order to verify the rationality of the theoretical derivation of the system frequency during the fault period, Figure 5The figure is a comparison chart of the system frequency simulation curve and theoretical curve. Figure 5 It can be seen that the theoretical value of the system frequency during the fault period is roughly the same as the simulated value. Since it takes a certain amount of time for the active power of the synchronous machine and the wind turbine to recover, the frequency does not reach its maximum value at the time of fault removal, but reaches its maximum value around 0.04s after the fault is removed. However, since the fault recovery time is short and the maximum frequency value differs by 0.06Hz, it can be considered that the system frequency reaches its maximum value when the fault is removed.

[0077] Figure 6 This is a comparison chart of the system frequency curve before and after the addition of energy storage. By comparing the initial frequency change rate and the maximum frequency, the correctness of the theoretical analysis of the system frequency dynamic characteristics before and after the addition of energy storage can be verified.

[0078] Without energy storage-type virtual inertia and virtual damping control, the frequency change curve of the wind turbine grid connection point is analyzed when the wind turbine voltage drops to different depths. By adding energy storage-type virtual inertia and virtual damping control, the virtual inertia and virtual damping parameters are adjusted to keep the wind turbine grid connection point frequency within a safe range. The power capacity of the energy storage system is calculated, and the correctness of the energy storage capacity method is verified through time domain simulation.

[0079] Figure 7 (a) Figure 7 (b) are the changing curves of system frequency when the wind turbine grid connection point drops to 0.9pu and 0.8pu, respectively, which are consistent with the theoretical analysis.

[0080] Figure 8 (a) Figure 8 (b) The system frequency curves and the required energy storage output active power curves before and after the addition of energy storage when the wind turbine grid connection point drops to 0.7 pu. At this point, the maximum frequency is 51.7 Hz, requiring additional energy storage control. At this point, the virtual inertia parameter and virtual damping parameter are both 0.25, and the energy storage output is 0.1346, accounting for 6.73%, which is basically consistent with the theoretical analysis.

[0081] Figure 9 (a) Figure 9 (b) The system frequency curves and the required storage output active power curves before and after adding energy storage when the wind turbine grid connection point drops to 0.5 pu, respectively. At this point, the maximum frequency is 52.6 Hz, requiring additional energy storage control. Due to the maximum energy storage capacity limit, if 20% of the energy storage is utilized and the virtual inertia parameter and virtual damping parameter are adjusted to 1, the maximum frequency can be reduced to 51.95 Hz, which is basically consistent with the theoretical analysis.

[0082] Through time-domain simulation analysis, it can be found that for a single-unit system containing a direct-drive wind turbine, the energy storage power capacity required under a short-circuit fault is roughly the same as the theoretically calculated value, verifying the correctness of the quantitative assessment method of energy storage capacity considering frequency support requirements and low-voltage ride-through.

[0083] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. Reference can be made to the common and similar parts between the various embodiments. For the systems disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the description is relatively simple, and the relevant parts can be referred to the method description.

[0084] This document uses specific examples to illustrate the principles and implementation methods of the present invention. The above examples are only intended to help understand the method and core concept of the present invention. At the same time, those skilled in the art will find that the specific implementation methods and application scopes may vary based on the concept of the present invention. In summary, the contents of this specification should not be construed as limiting the present invention.

Claims

1. A quantitative evaluation method for energy storage capacity considering frequency support requirements and low voltage ride-through, characterized by: Considering the frequency support requirements and low voltage ride-through control after a short-circuit fault, a quantitative assessment of energy storage capacity is conducted, including: Build a wind turbine grid-connected system with virtual inertia damping control and low-pressure ride-through control; Analyze the active power variation characteristics and system frequency dynamic characteristics when the wind turbine grid-connected voltage drops to different degrees; Quantitative analysis of the system frequency dynamic characteristics after adding virtual inertia damping control; Configure control parameters according to frequency response indicators; Considering low voltage ride-through and system frequency limitations, quantitatively analyze the energy storage capacity required for wind power transmission systems; The construction of the wind turbine grid-connected system including virtual inertia damping control and low voltage ride-through control specifically includes: The direct-drive wind turbine model includes a direct-drive permanent magnet generator, a machine-side converter, a grid-side converter and their control systems; In order to ensure that the wind turbine has the same inertia damping characteristics, the energy storage system is used to provide active power support for the wind turbine. The differential link of the system frequency is introduced to provide inertia support for the wind turbine, and the proportional link of the frequency is introduced to provide damping support for the wind turbine. The system frequency adopts the angular frequency of the wind turbine's grid connection point. The virtual inertia damping control strategy equation is as follows: Among them, P ESS1 、P ESS2 are the inertia response support power and primary frequency modulation support power provided by the energy storage device respectively; H vir 、D vir are the virtual inertia control coefficient and the virtual damping control coefficient respectively; Δf is the change of system frequency; P ESSref It is the active power reference value of the energy storage inverter.

2. The method for quantitatively evaluating energy storage capacity considering frequency support requirements and low voltage ride-through according to claim 1 is characterized by: The analysis of the active power variation characteristics and system frequency dynamic characteristics when the wind turbine grid-connected voltage drops to different degrees is as follows: During a short-circuit fault, the wind turbine active power and the wind turbine grid-connected voltage satisfy the relationship: Among them, P w is the active power output of the fan, k iq is the wind turbine reactive current regulation coefficient, k i is a constant, usually taken as 1.05, u gpu is the wind turbine grid-connected voltage during a short-circuit fault; The change in system active power during a short-circuit fault ΔP s for: Where ΔP G is the active power change of the synchronous machine during the short-circuit fault, P sw is the rated active power of the wind turbine, P wi is the active power output by the i-th wind turbine during the short-circuit fault, and m is the number of wind turbines; The time domain expression of the system frequency change curve when the system inertia damping takes effect during a short-circuit fault is: Where f0 is the rated frequency of the system, H s 、D s are the system inertia time constant and system damping parameter respectively, and t0 is the fault start time.

3. The method for quantitatively evaluating energy storage capacity considering frequency support requirements and low voltage ride-through according to claim 1 is characterized in that: The specific contents of the quantitative analysis of the system frequency dynamic characteristics after adding virtual inertia damping control are as follows: When virtual inertia and virtual damping control take effect during a short-circuit fault, the energy storage output active power P ESS Satisfy the following formula: Among them, f pll The frequency measured for the phase-locked loop; The frequency measured by the phase-locked loop is equal to the system frequency, that is, it is assumed that the phase-locked loop can accurately measure the real-time system frequency changes; The system frequency dynamic characteristics after adding virtual inertia damping control are obtained through the system frequency change characteristic curve without adding energy storage and the relationship between the energy storage output active power and the virtual inertia and virtual damping parameters.

4. The method for quantitatively evaluating energy storage capacity considering frequency support requirements and low voltage ride-through according to claim 1 is characterized in that: The control parameters are configured according to the frequency response index, and the specific contents include: Determining a system frequency response index, wherein the system frequency response index includes a maximum system frequency and an initial frequency change rate; The control parameters include virtual inertia parameters and virtual damping parameters; According to the frequency response index, the virtual inertia parameters and virtual damping parameters are adjusted so that the maximum frequency and the initial frequency change rate meet the frequency index requirements, thereby determining the virtual inertia and virtual damping parameters.

5. The method for quantitatively evaluating energy storage capacity considering frequency support requirements and low voltage ride-through according to claim 1 is characterized in that: Considering low voltage ride-through and system frequency limitations, a quantitative analysis of the energy storage capacity required for wind power transmission systems is conducted. Specific details include: The active power output by the energy storage is determined based on the relationship between the active power output by the energy storage, the virtual inertia damping parameter, and the system frequency; Considering the low voltage ride-through control of the energy storage system, the active power output of the energy storage is calculated when the grid-connected voltage drops to different levels, and the energy storage capacity assessment value is updated.

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