CN116365556A - A method and system for configuring energy storage capacity of a photovoltaic distribution network - Google Patents

Abstract

The invention belongs to the technical field of new energy power generation, and discloses an energy storage capacity configuration method and system of a photovoltaic-containing power distribution network, wherein the method detects the power of networking nodes of the power distribution network in real time and judges the state of photovoltaic energy storage capacity configuration equipment; dividing a capacity configuration mode into two capacity configuration storage libraries according to the state of the photovoltaic energy storage capacity configuration according to the judgment result; when the power grid networking node power judging module operates normally, performing first capacity configuration storage library control; and after the power reduction fault occurs to the power grid networking node power judging module, respectively controlling the photovoltaic converter and a second capacity configuration storage library of the energy storage capacity configuration device. The invention can realize stabilizing the fluctuation of the photovoltaic power generation power in normal operation through the partition capacity configuration mode and furthest provides reactive support for the power grid.

Description

A method and system for configuring energy storage capacity of a photovoltaic distribution network

Technical Field

The present invention belongs to the technical field of renewable energy power generation, and in particular relates to a method and system for configuring energy storage capacity of a photovoltaic power distribution network.

Background Art

With the rapid economic development, the continuous increase in electricity demand, the increasing scarcity of traditional energy and the deteriorating environment, large-scale grid-connected photovoltaic power generation has become a development trend.

However, photovoltaic power is significantly affected by natural resource conditions and climate conditions, and has the characteristics of volatility and intermittency, which to a certain extent causes disturbances and impacts to the connected distribution network, and even causes power to exceed the limit, affecting the safe, reliable and stable operation of the power grid. In order to maximize the use of light resources, photovoltaic power generation usually operates at a unity power factor, and energy storage has its unique advantages in balancing active power output. Therefore, configuring energy storage at the nodes connected to the photovoltaic distribution network can effectively adjust the power of the nodes connected to the distribution network. Therefore, how to configure the energy storage capacity of the photovoltaic distribution network has become a problem that urgently needs to be solved.

In recent years, there have been many methods for configuring energy storage capacity at home and abroad, but the general methods have the disadvantages of insufficient intuitiveness of energy storage configuration indicators and complex operation.

As the global climate and energy crisis becomes increasingly severe, renewable energy generation represented by photovoltaics has received widespread attention. However, due to the influence of natural conditions, the application of renewable energy generation also has certain limitations. It has its own shortcomings such as large output power fluctuations and weak ability to resist grid failures. If a storage system is equipped in a renewable energy power generation system, it can effectively increase the stability and reliability of the system and make up for the above defects.

With the continuous increase in the penetration rate of renewable energy power generation, in addition to ensuring that the power output of renewable energy itself remains stable, it must also have low power ride-through (LVRT) capabilities. The introduction of energy storage capacity configuration devices also provides a better solution to the problem of low power ride-through. According to the power and energy characteristics of the energy storage element itself, the energy storage element can be divided into two categories: power type and energy type. It is difficult for an energy storage system composed of a single energy storage element to meet the needs of both energy and power at the same time. Therefore, some scholars have proposed the concept of energy storage capacity configuration devices, such as energy storage capacity configuration devices composed of supercapacitors and batteries. When low power ride-through occurs, supercapacitor energy storage can absorb or release unbalanced power in a very short time, enhancing system stability. Battery energy storage can effectively absorb unbalanced energy and provide reactive power support to the nodes connected to the distribution network.

After adding the energy storage capacity configuration device, considering the characteristics of the energy storage system itself, it is necessary to effectively control the state of charge (SOC) of the energy storage battery when the system is operating normally and the power command distribution when the system fails. Many scholars have conducted research on this, but they have only considered how to maximize the reactive power compensation for the power drop point, and have not fully considered the charging and discharging characteristics of the energy storage unit in the hybrid energy storage, which may seriously damage the battery life. Therefore, how to feed back the state of charge of the energy storage battery to the charging and discharging command in real time to achieve the optimal scheduling of hybrid energy storage is still a key issue to be solved.

Through the above analysis, the problems and defects of the existing technology are as follows: the existing technology only considers how to compensate the power at the drop point to the maximum extent, and does not fully consider the charging and discharging characteristics of the energy storage unit in the hybrid energy storage. In addition, many scholars do not consider the real-time charge state of the hybrid energy storage when allocating the hybrid energy storage power instruction, which may also cause the energy storage battery to overcharge and discharge, which may seriously damage the battery life. At the same time, the existing hybrid energy storage capacity configuration mode is to put the two energy storage systems into operation at the same time, so that multiple energy storage devices will be put into operation when the power drops slightly, resulting in unnecessary waste of resources. In the event of a large power drop fault, in order to obtain a large reactive compensation in a short time to increase the power of the distribution network connection node, the previous strategy is to make the battery perform a large reactive power compensation, while superconducting magnetic energy storage and supercapacitors absorb and release active power. This will easily cause a shortage of active power in the system, thereby causing the frequency of the distribution network connection node to fluctuate, making the photovoltaic power generation system more likely to be disconnected from the grid. In addition, at the photovoltaic inverter level, the previous strategy was to maintain maximum power point tracking (MPPT) control under any operating state, but ignored the fact that when low power ride-through occurs, if the photovoltaic cells maintain maximum power output, the unbalanced power generated may increase, which brings difficulties to the regulation of energy storage during low power ride-through.

Summary of the invention

In view of the problems existing in the prior art, the present invention provides a method and system for configuring energy storage capacity of a photovoltaic distribution network.

The present invention is implemented as follows: a method for configuring energy storage capacity of a photovoltaic distribution network, the method for configuring energy storage capacity of a photovoltaic distribution network comprising the following steps:

S1, real-time detection of the power U _PCC of the nodes connected to the distribution network, and identification of the status of the photovoltaic energy storage capacity configuration equipment;

S2, based on the judgment result of S1, divides the capacity configuration mode into two capacity configuration storage repositories according to the state of the photovoltaic energy storage capacity configuration;

S3, when the power judgment module of the S1 power grid connection node operates normally, the first capacity configuration storage library is controlled;

S4, after a power drop failure occurs in the power judgment module of the S1 grid connection node, the second capacity configuration storage library of the photovoltaic converter and the energy storage capacity configuration device is controlled respectively.

Further, in S1, the power U _PCC of the connection node of the distribution network is detected in real time, and the state of the photovoltaic energy storage capacity configuration device is judged, as shown in the following formula:

Where, U _N is the grid-side rated power, the upper formula is for normal operation, and the lower formula is for a falling fault.

Further, in S2, the first capacity configuration storage repository is controlled as a normal system operation control to achieve photovoltaic power smoothing; the second capacity configuration storage repository is controlled as a fault state control to rapidly increase the power U _PCC of the distribution network connection node and maintain the DC bus power U _DC stable to achieve low power ride through.

Further, in S3, the first capacity configuration storage repository control is performed when the power judgment module of the S1 power grid connection node operates normally, including:

The unidirectional converter control system on the photovoltaic panel side works in the maximum power tracking MPPT mode to maximize the use of photovoltaic energy. Due to the fluctuation of light and temperature, the photovoltaic cells will produce unbalanced power fluctuations on the DC side. Considering this volatility, with 2.5 minutes as the time scale, the unbalanced power ΔP ₀ generated during this period is used as the energy storage reference power _PLH . The energy storage reference power is decomposed into a high-frequency part _PH and a low-frequency part _PL through the capacity configuration decomposition control strategy. The high-frequency part is absorbed by superconducting magnetic energy storage, and the low-frequency part is absorbed by liquid flow battery energy storage. Then, by detecting the initial state of charge SOC ₀ of the superconducting magnetic energy storage SMES and the liquid flow battery energy storage VRB, the SOC power control signal P _bat is obtained by descent control and fed back to the energy storage capacity configuration device, so as to realize the balanced control of the SOC of the energy storage capacity configuration device and the absorption of unbalanced power, and maintain the stable operation of the system.

The method of realizing power allocation of energy storage capacity configuration device by capacity configuration decomposition control strategy includes:

和最小值

以液流电池和超导磁储能组成的储能容量配置装置进行2.5min时间尺度的不平衡功率ΔP₀计算，如下式所示：(1) Real-time detection of the maximum active power output of the photovoltaic array within 2.5 minutes

and minimum value

The unbalanced power ΔP ₀ on a time scale of 2.5 min is calculated using the energy storage capacity configuration device composed of a flow battery and a superconducting magnetic energy storage device, as shown in the following formula:

为光伏发电系统的额定有功功率。In the formula,

is the rated active power of the photovoltaic power generation system.

(2) The obtained unbalanced power ΔP ₀ is used as the energy storage reference power _PLH , that is, _PLH = ΔP ₀ .

(3) The capacity configuration decomposition control strategy is used to decompose the energy storage reference power, and two groups of positive and negative white noises _Pz (t) and _-Pz (t) with a mean of 0 are added to the photovoltaic real-time active power _PPV (t):

Where, λ ₁ and λ ₂ are attenuation coefficients, which are 1.5 and 2.5 respectively; f is the oscillation frequency, which is 0.8; and t is the time.

即：The first-order function component of photovoltaic active power is obtained by the following formula:

Right now:

In the formula, P _PV (t) is the real-time detected output active power value of the photovoltaic cell array; P _z (t) is the white noise added to the photovoltaic active power, z = 1, 2, 3…, n, n is the logarithm of the added white noise; m _z is the amplitude of the white noise, which is 3~5dB.

通过下式进行集成平均后，分别得到N个容量配置混叠量

The obtained IMF components

After integrating and averaging through the following formula, we can get N capacity configuration aliasing quantities:

Wherein, j is a positive integer from 1 to N, P _j (t) is the jth pair of white noise added, and N is the number of all IMFs.

The division of the high-frequency and low-frequency parts of the capacity configuration aliasing amount is completed by the following formula:

Wherein, _PH is the high-frequency part of the energy storage reference power; _PL is the low-frequency part of the energy storage reference power.

The method comprises: detecting the initial charge states SOC _0-SMES and SOC _0-VRB of the superconducting magnetic energy storage SMES and the vanadium liquid flow battery energy storage VRB, obtaining an SOC power control signal by descending control and feeding it back to the energy storage capacity configuration device, so that the energy storage capacity configuration device can realize balanced and reasonable control of its SOC state, including:

(1) According to the initial state of charge SOC ₀ of the SMES and VRB energy storage units, the output power reference value is calculated using the descent control

Wherein, U _dcref is the reference value of DC bus power; P _SMES is the monitored real-time output active power of superconducting magnetic energy storage SMES, P _VRB is the monitored real-time output active power of vanadium liquid flow battery energy storage VRB; R _d-SMES and R _d-VRB are the droop coefficients of the hybrid energy storage module.

(2) Multiplying the obtained hybrid energy storage output power reference value and the hybrid energy storage output current reference value to obtain a feedback power signal P _bat :

为SEMS和VRB的输出电流参考值；m为整合系数，取5％。In the formula,

is the output current reference value of SEMS and VRB; m is the integration coefficient, which is 5%.

(3) Using the obtained feedback power signal P _bat and the obtained energy storage reference powers _PH and _PL , the final energy storage power instruction is calculated as follows:

Wherein, _P′H is the high-frequency part of the final energy storage reference power; _P′L is the low-frequency part of the final energy storage reference power.

(4) The hybrid energy storage control system works in the first capacity configuration storage bank control mode and adopts power outer loop control, that is, the power command is used to control the charging and discharging of the energy storage capacity configuration device, and the obtained _P′H and _P′L are used as the input reference values of the SMES and VRB power feedforward control respectively to smooth the active power fluctuation of the photovoltaic power supply output.

The method for controlling the first capacity configuration storage bin of the vanadium liquid flow battery energy storage VRB comprises:

The VRB battery bank bidirectional converter takes high power factor as the control target and works in the active leveling state. At this time, the active and reactive control links select the upper channel gating, the active current reference value i _P is calculated by the DC bus power U _dc , and the reactive current reference value i _q =0.

Further, in S4, after a power drop failure occurs in the power judgment module of the S1 power grid connection node, the second capacity configuration storage bank control of the photovoltaic converter is performed, including:

与实际直流母线功率测量值U_dc的差值ΔU_dc：During low power ride-through, the PV inverter will no longer work in MPPT mode, but will calculate the DC bus power reference value.

The difference ΔU _dc from the actual DC bus power measurement value U _dc is:

Using ΔU _dc as the input of the proportional integral controller PI in the grid-connected inverter control system, the duty cycle α of the unidirectional converter and the output active power reference value P _PV of the photovoltaic cell at this time are obtained by the following formula:

P _PV =αP _PV (t);

Where i _PV is the current output by the photovoltaic cell in real time, and P _PV (t) is the active power output by the photovoltaic cell in real time.

By controlling the duty cycle α of the unidirectional DC/DC, the photovoltaic cell outputs active power according to P _PV to maintain the stability of the DC bus power.

Further, in S4, after a power drop failure occurs in the power judgment module of the S1 power grid connection node, the second capacity configuration storage library control of the energy storage capacity configuration device includes:

The energy storage capacity configuration device adopts the strategy of superconducting magnetic energy storage system SMES priority regulation and vanadium liquid flow battery energy storage VRB supplementary regulation according to the depth of power drop; when the power drop depth is less than 40%, only SMES charging and discharging is used to maintain power stability, VRB is temporarily not put into operation, and SMES performs reactive power regulation; when the power drop depth is greater than 40%, VRB is put into operation, and VRB performs active power regulation, including:

(1) After a power drop fault occurs, an unbalanced power ΔP ₁ is generated between the system input and output:

The unbalanced power _ΔP1 is decomposed into high and low frequency parts _PH1 and _PL1 through the capacity configuration decomposition control strategy; the obtained energy storage power command is distributed to the energy storage capacity configuration device for power regulation, and _PH1 and _PL1 are used as the input reference values of SMES and VRB power feedforward control respectively.

(2) When the power drop depth is less than 40%, only the inverter on the SMES side performs the second capacity configuration storage bank control, and the reactive current reference value i _SMES output by the SMES energy storage is obtained by the following formula:

Where, P _H1 is the SMES power feedforward control input reference value; cosφ is the SMES power factor, which is 0.5.

Take i _SMES as the input of the proportional integral controller PI, and then perform pulse width modulation on the output signal of the PI controller through the PWM controller to obtain the reactive power Q _SMES that the SMES energy storage needs to absorb or emit:

Where α is the PWM modulation ratio, and X _ac is the AC side incoming line inductance.

By adjusting α through the current inner loop control, SMES can absorb or generate reactive power to the maximum extent according to Q _SMES .

(3) When the power drop depth is greater than 40%, when both energy storage systems are put into operation, taking into account the capacity constraints of the two energy storage systems, the high- and low-frequency power instructions in step (1) are used to track the energy storage charging and discharging status in real time, and the total margin of the hybrid energy storage system and its own maximum charge and discharge power limit are combined with the real-time SOC size of the energy storage system to allocate power to the two energy storage systems. By dynamically updating the charge and discharge power instructions of the energy storage capacity configuration device, high-quality scheduling tracking is achieved, including:

1) The real-time SOC size of the hybrid energy storage is obtained by the following formula, which are SOC _SMES (t) and SOC _VRB (t):

分别为SEMS储能和VRB储能的额定容量；t为时间；k为常系数，取1～2之间。In the formula,

are the rated capacities of SEMS energy storage and VRB energy storage respectively; t is time; k is a constant coefficient between 1 and 2.

如下式所示：2) The high and low frequency reference power _PH1 , _PL1 obtained by the capacity configuration decomposition control strategy in step (1) and the real-time SOC size of the hybrid energy storage are comprehensively optimized through the following formula to obtain the dispatching power reference instruction of SMES and VRB:

As shown below:

Where P _SP (t) is the system dispatching power, which is the target power curve given by the upper-level power grid operation department; Δt is the working step length, which is 2.5 min; T _V is the filtering time constant, which is 26.02.

分别反馈到SMES和VRB逆变器控制信号输入值当中，实现对两种储能进行功率指令的动态更新，如下式所示：3) The dispatch power reference instructions of SMES and VRB are obtained

The feedback is respectively fed back to the SMES and VRB inverter control signal input values to realize the dynamic update of the power instructions for the two energy storages, as shown in the following formula:

为SMES更新后的比例积分控制器输入值，

为VRB更新后的比例积分控制器输入值。In the formula,

Updated proportional-integral controller input values for SMES,

Enter the values for the VRB updated proportional-integral controller.

进行步骤(2)中的无功功率控制；VRB则根据更新后的功率参考值

进行如下有功功率控制：SMES updates the reactive current reference value

Perform reactive power control in step (2); VRB then adjusts the power reference value according to the updated power reference value.

Perform active power control as follows:

作为VRB比例积分控制器PI的输入，经控制器调节后，运用下式计算出脉冲宽度调制器的输入量α_PWM：The updated power reference value

As the input of VRB proportional integral controller PI, after being adjusted by the controller, the input quantity α _PWM of the pulse width modulator is calculated using the following formula:

After being adjusted by the pulse width modulator, the VRB battery is charged/discharged according to P _VRB :

分别为VRB蓄电池的有功、无功电流参考值。In the formula,

They are respectively the active and reactive current reference values of VRB battery.

Another object of the present invention is to provide an energy storage capacity configuration system for a photovoltaic distribution network using the energy storage capacity configuration method for a photovoltaic distribution network, wherein the energy storage capacity configuration system for a photovoltaic distribution network comprises:

The system status identification module is used to detect the power U _PCC of the distribution network connection node in real time and to identify the status of the photovoltaic energy storage capacity configuration equipment;

A capacity configuration mode division module, used for dividing the capacity configuration mode into two capacity configuration storage repositories according to the state of the photovoltaic energy storage capacity configuration based on the judgment result of the system state judgment module;

A first capacity configuration storage repository control module, used for controlling the first capacity configuration storage repository when the power grid connection node power judgment module of the system state judgment module operates normally;

The second capacity configuration storage repository control module is used to control the second capacity configuration storage repository of the photovoltaic converter and the energy storage capacity configuration device respectively after a power reduction failure occurs in the power grid connection node power judgment module of the system state judgment module.

Another object of the present invention is to provide a computer device, the computer device comprising a memory and a processor, the memory storing a computer program, and when the computer program is executed by the processor, the processor performs the following steps:

Real-time detection of the power U _PCC of the distribution network connection node, and determination of the state of the photovoltaic energy storage capacity configuration device; based on the determination result, the capacity configuration mode is divided into two capacity configuration storage repositories according to the state of the photovoltaic energy storage capacity configuration; when the power grid connection node power determination module operates normally, the first capacity configuration storage repositories are controlled; when the power grid connection node power determination module has a power drop fault, the second capacity configuration storage repositories of the photovoltaic converter and the energy storage capacity configuration device are respectively controlled.

Another object of the present invention is to provide a computer-readable storage medium storing a computer program, wherein when the computer program is executed by a processor, the processor executes the following steps:

Real-time detection of the power U _PCC of the distribution network connection node, and determination of the state of the photovoltaic energy storage capacity configuration device; based on the determination result, the capacity configuration mode is divided into two capacity configuration storage repositories according to the state of the photovoltaic energy storage capacity configuration; when the power grid connection node power determination module operates normally, the first capacity configuration storage repositories are controlled; when the power grid connection node power determination module has a power drop fault, the second capacity configuration storage repositories of the photovoltaic converter and the energy storage capacity configuration device are respectively controlled.

Another object of the present invention is to provide an information data processing terminal, which is used to implement the energy storage capacity configuration system containing the photovoltaic distribution network.

Combining all the above technical solutions, the advantages and positive effects of the present invention are as follows:

The difficulty of solving the above problems and defects is:

In order to solve the above problems and defects, it is necessary to improve and perfect the capacity configuration mode of photovoltaic inverters and energy storage capacity configuration devices. During this period, it is necessary to monitor the electrical quantities of distribution network connection nodes and energy storage systems in real time, judge the operating status based on the monitored quantities, and realize dynamic switching of the capacity configuration mode of the energy storage capacity configuration device in view of the different control targets during normal operation and failure of photovoltaic power generation systems, which requires high data processing and analysis capabilities; more importantly, the charging and discharging characteristics of different energy storage battery types in the energy storage capacity configuration device are different, and the photovoltaic power generation system has high time response requirements for low power ride-through control. Therefore, the energy storage system needs to quickly adjust the charging and discharging power in a targeted manner according to the differences in the characteristics of different energy storage battery types to keep the photovoltaic system in stable operation. How to reasonably utilize the characteristics of various energy storage batteries for reasonable and efficient coordinated control may be difficult in actual operation.

Solving the above problems and defects can smooth out power fluctuations during normal system operation, keep the energy storage charge state within a reasonable range, reduce factors that make the system unstable when low power ride-through occurs, minimize the size of unbalanced power, and enable the energy storage capacity configuration device to quickly and effectively adjust the system operation state while taking into account its own charging and discharging characteristics. While ensuring that the photovoltaic system does not go offline, the charge state of the energy storage battery is maintained within a normal range, effectively extending the battery life. In addition, hierarchical control is adopted according to the degree of power reduction, which greatly reduces the battery consumption and achieves significant economic improvements.

The energy storage capacity configuration method of the photovoltaic distribution network provided by the present invention relates to hybrid energy storage and photovoltaic grid-connected systems. Based on hybrid energy storage, improvements are made on the basis of traditional single-element energy storage systems. The present invention first constructs a photovoltaic new energy power generation system consisting of a photovoltaic panel array, a grid-connected inverter, and superconducting magnetic energy storage (SMES) and liquid flow battery (VRB) energy storage connected in parallel on the DC bus side. The capacity configuration mode proposed by the present invention improves the power distribution of the energy storage capacity configuration device and the inverter capacity configuration mode. The strategy of the present invention includes two capacity configuration storage libraries. The first capacity configuration storage library is used to control the smoothing of photovoltaic power generation power fluctuations during the normal operation of the photovoltaic power generation system; the second capacity configuration storage library is used to control the low-power crossing of the photovoltaic power generation system after the power of the power grid decreases. Through the above-mentioned hybrid energy storage coordinated control, the purpose of optimal charging and discharging of the energy storage battery is achieved. The energy storage capacity configuration strategy for the photovoltaic distribution network based on hybrid energy storage provided by the present invention takes into account both the smoothing of photovoltaic power generation power fluctuations during normal operation of the photovoltaic power generation system and the photovoltaic low-power ride-through after the power of the grid decreases, ensuring that the system does not operate off-grid, achieving more reasonable power command allocation and optimal charging and discharging of the energy storage system, thereby improving the stability and economy of the system operation.

In response to the problem of low power ride-through in photovoltaic grid-connected power generation systems, the present invention proposes a storage capacity configuration strategy for a photovoltaic distribution network based on hybrid energy storage. This strategy improves on the low power ride-through of a traditional single energy storage system-assisted photovoltaic power station, and achieves low power ride-through by connecting a storage capacity configuration device consisting of a superconducting magnetic energy storage system (SMES) and a liquid flow battery (VRB) energy storage system in parallel on the DC side of the photovoltaic power generation system; not only that, this strategy improves the power allocation problem of the energy storage capacity configuration device and the capacity configuration mode of the bidirectional converter connected to the two energy storage units; the present invention adopts a partition control method to control the system in two states; the first capacity configuration storage library controls, and when the system is operating normally, the maximum power tracking of photovoltaic power generation is achieved by controlling the unidirectional converter on the photovoltaic panel side, and the empirical capacity configuration decomposition (EMD) method is used to The unbalanced power generated on the photovoltaic panel side is divided, and the energy storage capacity configuration device is used to absorb the unbalanced power. At the same time, the energy storage battery SOC reduction control is used to feed back the power signal to the control system to realize the balanced control of the energy storage battery SOC; the second capacity configuration storage storage control, when the power drops on the grid side, the unidirectional converter on the photovoltaic panel side switches to constant voltage control, and the superconducting magnetic energy storage and liquid flow battery both switch the capacity configuration mode. According to the depth of power drop, the SMES priority adjustment and VRB supplementary strategy are adopted. When the two energy storages are put into operation at the same time, the total margin of the energy storage, its own maximum charge and discharge power limit and the real-time SOC state are combined to adopt a coordinated power allocation strategy to achieve high-quality scheduling and tracking. The present invention can realize the smoothing of photovoltaic power generation power fluctuations during normal operation through the partition capacity configuration mode. After the power of the grid drops, the system will not be disconnected from the grid for a short time and provide reactive support to the grid to the maximum extent, and the DC bus power is stabilized within a certain range.

BRIEF DESCRIPTION OF THE DRAWINGS

In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments of the present invention. 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 creative work.

FIG1 is a flow chart of a method for configuring energy storage capacity of a photovoltaic distribution network provided in an embodiment of the present invention.

2 is a block diagram of a system for configuring energy storage capacity including a photovoltaic distribution network according to an embodiment of the present invention;

3 is a schematic diagram of SOC changes of SMES and VRB provided in an embodiment of the present invention;

In the figure: 1. System status identification module; 2. Capacity configuration mode division module; 3. First capacity configuration repository control module; 4. Second capacity configuration repository control module.

DETAILED DESCRIPTION

In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

In view of the problems existing in the prior art, the present invention provides a method, system, device and terminal for configuring energy storage capacity of a photovoltaic distribution network. The present invention is described in detail below with reference to the accompanying drawings.

As shown in FIG1 , the energy storage capacity configuration method of the photovoltaic distribution network provided in the embodiment of the present invention includes the following steps:

S101, real-time detection of the power U _PCC of the nodes connected to the distribution network, and identification of the status of the photovoltaic energy storage capacity configuration equipment;

S102, based on the result of S101, dividing the capacity configuration mode into two capacity configuration storage repositories according to the state of the photovoltaic energy storage capacity configuration;

S103, when the power grid connection node power judgment module S101 operates normally, the first capacity configuration storage library is controlled;

S104, after a power drop fault occurs in the power judgment module of the grid connection node, control is performed on the second capacity configuration storage bank of the photovoltaic converter;

S105, after a power reduction failure occurs in the power judgment module of the grid connection node, the second capacity configuration storage bank of the energy storage capacity configuration device is controlled.

As shown in FIG2 , the energy storage capacity configuration system including a photovoltaic distribution network provided in an embodiment of the present invention includes:

System status identification module 1, used for real-time detection of the power U _PCC of the distribution network connection node, and identification of the status of the photovoltaic energy storage capacity configuration device;

A capacity configuration mode division module 2 is used to divide the capacity configuration mode into two capacity configuration storage repositories according to the state of the photovoltaic energy storage capacity configuration based on the judgment result of the system state judgment module;

A first capacity configuration repository control module 3, used to control the first capacity configuration repository when the system state determination module and the power grid connection node power determination module operate normally;

The second capacity configuration repository control module 4 is used to control the second capacity configuration repository of the photovoltaic converter and the energy storage capacity configuration device respectively after a power reduction failure occurs in the power grid connection node power judgment module of the system state judgment module.

The embodiment of the present invention proposes a strategy for energy storage capacity configuration of a photovoltaic distribution network based on hybrid energy storage, which is an improvement on the traditional single-element energy storage system. First, a photovoltaic new energy power generation system consisting of a photovoltaic panel array, a grid-connected inverter, and superconducting magnetic energy storage (SMES) and liquid flow battery (VRB) energy storage connected in parallel on the DC bus side is constructed. The capacity configuration mode proposed in the present invention improves the power distribution of the energy storage capacity configuration device and the inverter capacity configuration mode. The strategy includes two capacity configuration storage libraries. The first capacity configuration storage library is used to control the smoothing of photovoltaic power generation power fluctuations during the normal operation of the photovoltaic power generation system; the second capacity configuration storage library is used to control the low-power ride-through of the photovoltaic power generation system after the power of the power grid decreases. Through the above-mentioned hybrid energy storage coordinated control, the purpose of optimal charging and discharging of the energy storage battery is achieved.

The technical method adopted by the present invention is as follows:

Step 1: Real-time detection of the power U _PCC of the nodes connected to the distribution network to determine the operating status of the photovoltaic energy storage capacity configuration equipment, as shown in the formula:

Where, U _N is the grid-side rated power, the upper formula is for normal operation, and the lower formula is for a falling fault.

Step 2: Based on the result of Step 1, the capacity configuration mode is divided into two capacity configuration storage repositories according to the state of the photovoltaic energy storage capacity configuration: the first capacity configuration storage repositories are controlled as the normal operation control of the system to achieve photovoltaic power smoothing; the second capacity configuration storage repositories are controlled as the fault state control to rapidly increase the power U _PCC of the distribution network connection node and keep the DC bus power U _DC stable to achieve low power ride through.

Step 3: When the power judgment module of the grid-connected node in Step 1 operates normally, the first capacity configuration storage bank is controlled; at this time, the photovoltaic grid-connected inverter controls the photovoltaic power generation system to work in the maximum power point tracking (MPPT) mode to maximize the use of solar energy. However, due to the fluctuation of light and temperature, the photovoltaic output will produce power fluctuations. Considering this volatility, the unbalanced power ΔP ₀ generated during this period of time is taken as the energy storage reference power _PLH with a time scale of 2.5 minutes. Then, the energy storage reference power _PLH is decomposed into a high-frequency part _PH and a low-frequency part _PL through empirical capacity configuration decomposition (EMD). The high-frequency part is absorbed by superconducting magnetic energy storage, and the low-frequency part is absorbed by liquid flow battery energy storage. The specific steps are as follows:

和最小值

以液流电池和超导磁储能组成的储能容量配置装置进行2.5min时间尺度的不平衡功率ΔP₀计算，如式所示：S1: Real-time detection of the maximum active power output of the photovoltaic array within 2.5 minutes

and minimum value

The unbalanced power ΔP ₀ on a time scale of 2.5 min is calculated using the energy storage capacity configuration device composed of a flow battery and a superconducting magnetic energy storage device, as shown in the formula:

为光伏发电系统的额定有功功率。In the formula

is the rated active power of the photovoltaic power generation system.

S2: The obtained unbalanced power ΔP ₀ is used as the energy storage reference power _PLH , that is, _PLH = ΔP ₀ .

S3: Use Empirical Decomposition (EMD) to decompose the energy storage reference power.

First, two sets of positive and negative white noises _Pz (t) and _-Pz (t) with a mean of 0 are added to the real-time photovoltaic active power _PPV (t):

Where λ ₁ and λ ₂ are attenuation coefficients, which are 1.5 and 2.5 respectively; f is the oscillation frequency, which is 0.8; and t is the time.

即：Then the first-order function component of photovoltaic active power is obtained by the following formula:

Right now:

In the formula, P _PV (t) is the real-time detected output active power value of the photovoltaic cell array; P _z (t) is the white noise added to the photovoltaic active power, z = 1, 2, 3…, n, n is the logarithm of the added white noise; m _z is the amplitude of the white noise, generally 3 to 5 dB.

通过(5)式进行集成平均后，分别得到N个容量配置混叠量

The IMF components obtained from (4)

After integrating and averaging through formula (5), we can obtain N capacity configuration aliasing quantities:

Where j is a positive integer from 1 to N, P _j (t) is the jth pair of white noise added, and N is the number of all IMFs.

Finally, the high-frequency and low-frequency parts of the capacity configuration aliasing amount are divided by the following formula:

Where: _PH is the high-frequency part of the energy storage reference power; _PL is the low-frequency part of the energy storage reference power;

At the same time, by detecting the initial charge states SOC _0-SMES and SOC _0-VRB of the superconducting magnetic energy storage SMES and the vanadium liquid flow battery energy storage VRB, the SOC power control signal is obtained by using the descent control and fed back to the energy storage capacity configuration device, so that the energy storage capacity configuration device can achieve balanced and reasonable control of its SOC state. The specific method is as follows

S1, according to the initial state of charge SOC ₀ of the SMES and VRB energy storage units, calculate their output power reference value using descent control

Wherein, U _dcref is the reference value of DC bus power; P _SMES is the monitored real-time output active power of superconducting magnetic energy storage SMES, P _VRB is the monitored real-time output active power of vanadium liquid flow battery energy storage VRB; R _d-SMES and R _d-VRB are the droop coefficients of the hybrid energy storage module.

S2, multiplying the hybrid energy storage output power reference value obtained by the above formula with the hybrid energy storage output current reference value to obtain a feedback power signal P _bat :

为SEMS和VRB的输出电流参考值；m为整合系数，取5％。in

is the output current reference value of SEMS and VRB; m is the integration coefficient, which is 5%.

S3, using the feedback power signal P _bat obtained from the above formula and the energy storage reference power _PH and _PL obtained from formulas (6) and (7), the final energy storage power instruction can be calculated as follows:

Where _P′H is the high-frequency part of the final energy storage reference power; _P′L is the low-frequency part of the final energy storage reference power.

Finally, the hybrid energy storage control system works in the first capacity configuration storage bank control mode, adopts power outer loop control, that is, uses power instructions to control the charging and discharging of the energy storage capacity configuration device, and uses P′ _H and P′ _L obtained in S3 as SMES and VRB power feedforward control input reference values, respectively, to smooth the active power fluctuation of the photovoltaic power supply output.

Step 4: After a power drop failure occurs in the power judgment module of the grid connection node in Step 1, the second capacity configuration storage bank of the photovoltaic converter is controlled:

与实际直流母线功率测量值U_dc的差值ΔU_dc：At this time, the photovoltaic inverter will no longer work in MPPT mode, but calculate the DC bus power reference value

The difference ΔU _dc from the actual DC bus power measurement value U _dc is:

Taking ΔU _dc as the input of the proportional integral controller (PI) in the grid-connected inverter control system, the duty cycle α of the unidirectional converter and the output active power reference value P _PV of the photovoltaic cell at this time are obtained by the following formula (12):

P _PV ＝αP _PV (t) (12)

Where i _PV is the current output by the photovoltaic cell in real time, and P _PV (t) is the active power output by the photovoltaic cell in real time.

At this time, the duty cycle α of the unidirectional DC/DC is controlled to make the photovoltaic cell output active power according to P _PV to maintain the stability of the DC bus power;

Step 5: After a power drop failure occurs in the power judgment module of the power grid connection node in Step 1, the second capacity configuration storage bank of the energy storage capacity configuration device is controlled;

The energy storage capacity configuration device adopts the strategy of giving priority to the superconducting magnetic energy storage system SMES and supplementary regulation of the vanadium liquid flow battery energy storage VRB according to the depth of power drop; when the power drop depth is less than 40%, only the SMES charging and discharging is used to maintain power stability, and the VRB is temporarily not put into operation. At this time, the SMES performs reactive power regulation; when the power drop depth is greater than 40%, the VRB is put into operation, and at this time, the VRB performs active power regulation.

The specific steps are as follows:

S1, after a power drop fault occurs, an unbalanced power ΔP ₁ will be generated between the system input and output:

Using the same method in Step 3, the unbalanced power _ΔP1 is decomposed into high-frequency and low-frequency parts _PH1 and _PL1 by using EMD (2) to (7). The energy storage power command obtained is assigned to the energy storage capacity configuration device for power regulation. _PH1 and _PL1 are used as the input reference values of SMES and VRB power feedforward control, respectively.

S2, when the power drop depth is less than 40%, only the inverter on the superconducting magnetic energy storage SMES side performs the second capacity configuration storage bank control, and the reactive current reference value i _SMES output by the SMES energy storage is obtained by the following formula:

Wherein, P _H1 is the SMES power feedforward control input reference value obtained by S1, and cosφ is the power factor of the SMES, which is taken as 0.5 in the present invention.

Take i _SMES as the input of the proportional integral controller (PI), and then perform pulse width modulation on the output signal of the PI controller through the PWM controller to obtain the reactive power Q _SMES that the SMES energy storage needs to absorb or emit, as shown in the following formula:

Where α is the PWM modulation ratio, and X _ac is the AC side incoming line inductance.

By adjusting α through the current inner loop control, SMES can absorb or generate reactive power to the maximum extent according to Q _SMES .

S3, when the power drop depth is greater than 40%, both energy storages are put into operation. Considering the capacity constraints of the two energy storages, the high and low frequency power instructions in S1 are used to track the energy storage charge and discharge status in real time. Combined with the total margin of the hybrid energy storage and its own maximum charge and discharge power limit and the real-time SOC size of the energy storage, power is allocated to the two energy storage systems. The dynamic update of the charge and discharge power instructions of the energy storage capacity configuration device is used to achieve high-quality scheduling tracking. The specific steps are as follows:

A, the real-time SOC size of the hybrid energy storage is obtained by the following formula, which are SOC _SMES (t) and SOC _VRB (t):

分别为SEMS储能和VRB储能的额定容量；t为时间；k为常系数，一般取1-2之间。In the formula

are the rated capacities of SEMS energy storage and VRB energy storage respectively; t is time; k is a constant coefficient, generally between 1 and 2.

如下式(17)所示：B. The high and low frequency reference power _PH1 , _PL1 obtained by the empirical capacity decomposition (EMD) in S1 and the real-time SOC size of the hybrid energy storage are comprehensively optimized through the following formula to obtain the dispatch power reference instruction of SMES and VRB

As shown in the following formula (17):

P _SP (t) is the system dispatching power, which is generally the target power curve given by the superior power grid operation department; Δt is the working step length, which is 2.5min; T _V is the filtering time constant, which is 26.02.

分别反馈到SMES和VRB逆变器控制信号输入值当中，实现对两种储能进行功率指令的动态更新，如下式所示：C, the dispatch power reference instructions of SMES and VRB are obtained

The feedback is respectively fed back to the SMES and VRB inverter control signal input values to realize the dynamic update of the power instructions for the two energy storages, as shown in the following formula:

为SMES更新后的比例积分控制器输入值，

为VRB更新后的比例积分控制器输入值。In the formula

Updated proportional-integral controller input values for SMES,

Enter the values for the VRB updated proportional-integral controller.

进行S2中的无功功率控制；VRB则根据更新后的功率参考值

进行如下有功功率控制：At this time, SMES uses the updated reactive current reference value

Perform reactive power control in S2; VRB uses the updated power reference value

Perform active power control as follows:

作为VRB比例积分控制器(PI)的输入，经控制器调节后，运用下式计算出脉冲宽度调制器的输入量α_PWM：At this time, the updated power reference value

As the input of VRB proportional integral controller (PI), after being adjusted by the controller, the input quantity α _PWM of the pulse width modulator is calculated using the following formula:

After being adjusted by the pulse width modulator, the VRB battery is charged/discharged according to P _VRB :

分别为VRB蓄电池的有功、无功电流参考值。In the formula

They are respectively the active and reactive current reference values of VRB battery.

The energy storage capacity configuration device quickly and effectively absorbs the unbalanced power ΔP ₁ according to the above updated instructions, so that the photovoltaic power generation system can better achieve low voltage ride-through; at the same time, it can also ensure that the SOC state of the energy storage system is maintained within the specified range in this process, reducing the life loss of the energy storage battery to a certain extent.

The technical solution of the present invention is further described below in conjunction with simulation experiments.

The specific parameters of the model built on the MATLAB/Simulink simulation platform are as follows: In the established simulation model, the system phase power is 220 V. During normal operation, the light intensity drops from 1000 to 500 in 0.2 s and recovers to 1000 in 0.3 s. During the low-power ride-through, the power drops during the [0.2 s, 0.4 s] period due to a fault. When the photovoltaic cell (PV) unit works in the maximum power tracking mode (MPPT), the maximum output power is 4kW; the DC side capacitor power is set at 500V, the rated power of the liquid flow battery energy storage VRB is 300kW, the rated power is 700V, the rated current is 430A, the rated capacity of the superconducting magnetic energy storage SMES is 1.08MJ, the superconducting initial current is 300A, and the superconducting maximum current is 600A; the superconducting magnetic energy storage SOC ₀ is 50%, the liquid flow battery SOC ₀ is 90%, the number of all IMFs and the logarithm of white noise N are 10, the integration coefficient m is 0.375, the droop coefficients R _d-SMES and R _d-VRB are 1.5 and 0.25 respectively, the DC bus power reference value U _dcref is 800V, the charging factor k is 1.03, and the filtering time constant T _V is 26.02.

According to the simulation results, the SMES system generates the maximum inductive reactive power to suppress the DC bus power at 800V, thereby performing the maximum reactive compensation. The DC bus power has only a short-term fluctuation of 0.05s when low-power ride-through occurs, and the fluctuation amplitude is only 70V, both within the specified range. It can be judged that the energy storage capacity configuration device uses the reactive margin to inject 415A of reactive current into the system, which plays a certain role in reducing the reactive configuration capacity and supporting the power recovery of the power grid. It can be seen from Figure 3 that in the process of hybrid energy storage coordinated control, the SOC change amplitude of the energy storage unit is less than 0.1%, which is kept within a reasonable range and is conducive to extending the battery life.

In summary, the energy storage capacity configuration strategy for the photovoltaic distribution network based on hybrid energy storage provided in the embodiment of the present invention takes into account both the smoothing of photovoltaic power generation power fluctuations during normal operation of the photovoltaic power generation system and the photovoltaic low-power ride-through after the power of the grid decreases, ensuring that the system does not operate off-grid, and achieving a more reasonable power command allocation and optimal charging and discharging of the energy storage system.

In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When the use is implemented in whole or in part in the form of a computer program product, the computer program product includes one or more computer instructions. When the computer program instructions are loaded or executed on a computer, the process or function described in the embodiment of the present invention is generated in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions may be transmitted from one website site, computer, server or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL) or wireless (e.g., infrared, wireless, microwave, etc.) mode) to another website site, computer, server or data center. The computer-readable storage medium may be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more available media integrated. The available medium may be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid-state hard disk Solid State Disk (SSD)), etc.

The above description is only a specific implementation mode of the present invention, but the protection scope of the present invention is not limited thereto. Any modifications, equivalent substitutions and improvements made by any technician familiar with the technical field within the technical scope disclosed by the present invention and within the spirit and principle of the present invention should be covered by the protection scope of the present invention.

Claims (10)

1. A method for configuring energy storage capacity of a photovoltaic distribution network, characterized in that the method comprises the following steps: S1, real-time detection of the power of the nodes connected to the distribution network, and identification of the status of the photovoltaic energy storage capacity configuration equipment; S2, based on the judgment result of S1, divides the capacity configuration mode into two capacity configuration storage repositories according to the state of the photovoltaic energy storage capacity configuration; S3, when the power judgment module of the S1 power grid connection node operates normally, the first capacity configuration storage library is controlled; S4, after a power drop failure occurs in the power judgment module of the S1 grid connection node, the second capacity configuration storage library of the photovoltaic converter and the energy storage capacity configuration device is controlled respectively. 2. The method for configuring energy storage capacity of a photovoltaic distribution network according to claim 1, characterized in that, in S1, the real-time detection of the power of the distribution network connection nodes is used to determine the state of the photovoltaic energy storage capacity configuration device, as shown in the following formula:

In the formula, U _N is the grid-side rated power, U _PCC is the power of the distribution network connection node, 0.9U _N ≤U _PCC ≤1.1U _N indicates normal operation, and U _PCC <0.9U _N indicates a decreasing fault. 3. The energy storage capacity configuration method for a photovoltaic distribution network according to claim 1 is characterized in that, in S2, the first capacity configuration storage repository is controlled as a normal system operation control to achieve photovoltaic power smoothing; in S4, the second capacity configuration storage repository is controlled as a fault state control to rapidly increase the power U _PCC of the distribution network connection node and maintain the DC bus power U _DC stable to achieve low power ride through. 4. The method for configuring energy storage capacity of a photovoltaic distribution network according to claim 1, characterized in that, in S3, when the power judgment module of the S1 power grid node operates normally, the first capacity configuration storage repository control is performed, comprising: The unidirectional converter control system on the photovoltaic panel side works in the maximum power tracking MPPT mode to maximize the use of photovoltaic energy. Due to the fluctuation of light and temperature, the photovoltaic cells will produce unbalanced power fluctuations on the DC side. Considering this volatility, with 2.5 minutes as the time scale, the unbalanced power ΔP ₀ generated during this period is used as the energy storage reference power _PLH . The energy storage reference power is decomposed into a high-frequency part _PH and a low-frequency part _PL through the capacity configuration decomposition control strategy. The high-frequency part is absorbed by superconducting magnetic energy storage, and the low-frequency part is absorbed by liquid flow battery energy storage. Then, by detecting the initial state of charge SOC ₀ of the superconducting magnetic energy storage SMES and the liquid flow battery energy storage VRB, the SOC power control signal P _bat is obtained by descent control and fed back to the energy storage capacity configuration device, so as to realize the balanced control of the SOC of the energy storage capacity configuration device and the absorption of unbalanced power, and maintain the stable operation of the system. 5. The method for configuring energy storage capacity of a photovoltaic power distribution network according to claim 4, wherein the control strategy for decomposing the capacity configuration comprises: (1) Real-time detection of the maximum active power output of the photovoltaic array within 2.5 minutes

and minimum value

The unbalanced power ΔP ₀ on a time scale of 2.5 min is calculated using the energy storage capacity configuration device composed of a flow battery and a superconducting magnetic energy storage device, as shown in the following formula:

In the formula,

is the rated active power of the photovoltaic power generation system; (2) The obtained unbalanced power ΔP ₀ is used as the energy storage reference power _PLH , that is, _PLH = ΔP ₀ ; (3) The capacity configuration decomposition control strategy is used to decompose the energy storage reference power, and two groups of positive and negative white noises _Pz (t) and _-Pz (t) with a mean of 0 are added to the photovoltaic real-time active power _PPV (t):

In the formula, λ ₁ and λ ₂ are attenuation coefficients, which are 1.5 and 2.5 respectively; f is the oscillation frequency, which is 0.8; t is the time; The first-order function component of photovoltaic active power is obtained by the following formula:

Right now:

In the formula, P _PV (t) is the real-time detected output active power value of the photovoltaic cell array; P _z (t) is the white noise added to the photovoltaic active power, z = 1, 2, 3…, n, n is the logarithm of the added white noise; m _z is the amplitude of the white noise, which is 3~5dB. 6. The method for configuring energy storage capacity of a photovoltaic distribution network according to claim 5, characterized in that the obtained IMF component

After integrating and averaging through the following formula, we can get N capacity configuration aliasing quantities:

Where j is a positive integer from 1 to N, P _j (t) is the jth pair of white noise added, and N is the number of all IMFs; The division of the high-frequency and low-frequency parts of the capacity configuration aliasing amount is completed by the following formula:

Wherein, _PH is the high-frequency part of the energy storage reference power; _PL is the low-frequency part of the energy storage reference power. 7. The method for configuring energy storage capacity of a photovoltaic power distribution network according to claim 4, characterized in that detecting the initial state of charge SOC ₀ of the superconducting magnetic energy storage SMES and the liquid flow battery energy storage VRB comprises: The SOC power control signal obtained by the descent control is fed back to the energy storage capacity configuration device, so that the energy storage capacity configuration device can achieve balanced and reasonable control of the state of its SOC, including: (1) According to the initial state of charge SOC ₀ of the SMES and VRB energy storage units, the output power reference value is calculated using the descent control

Wherein, U _dcref is the reference value of DC bus power; P _SMES is the real-time output active power of the monitored superconducting magnetic energy storage SMES, P _VRB is the real-time output active power of the monitored vanadium liquid flow battery energy storage VRB; R _d-SMES , R _d-VRB are the droop coefficients of the hybrid energy storage module; (2) Multiplying the obtained hybrid energy storage output power reference value and the hybrid energy storage output current reference value to obtain a feedback power signal P _bat :

In the formula,

is the output current reference value of SEMS and VRB; m is the integration coefficient, which is 5%; (3) Using the obtained feedback power signal P _bat and the obtained energy storage reference powers _PH and _PL , the final energy storage power instruction is calculated as follows:

Wherein, _P′H is the high-frequency part of the final energy storage reference power; _P′L is the low-frequency part of the final energy storage reference power; (4) The hybrid energy storage control system works in the first capacity configuration storage bank control mode and adopts power outer loop control, that is, the power command is used to control the charging and discharging of the energy storage capacity configuration device, and the obtained P′ _H and P′ _L are used as the input reference values of SMES and VRB power feedforward control respectively to smooth the active power fluctuation of the photovoltaic power supply output; The method for controlling the first capacity configuration storage bin of the vanadium liquid flow battery energy storage VRB comprises: The VRB battery bank bidirectional converter takes high power factor as the control target and works in the active leveling state. At this time, the active and reactive control links select the upper channel gating, the active current reference value i _P is calculated by the DC bus power U _dc , and the reactive current reference value i _q =0. 8. The method for configuring energy storage capacity of a photovoltaic power distribution network according to claim 1, wherein in S4, the second capacity configuration storage bank control of the photovoltaic converter is performed, comprising: During low power ride-through, the PV inverter will no longer work in MPPT mode, but will calculate the DC bus power reference value.

The difference ΔU _dc from the actual DC bus power measurement value U _dc is:

Using ΔU _dc as the input of the proportional integral controller PI in the grid-connected inverter control system, the duty cycle α of the unidirectional converter and the output active power reference value P _PV of the photovoltaic cell at this time are obtained by the following formula:

P _Pv =αP _PV (t); Where i _PV is the current output by the photovoltaic cell in real time, and P _PV (t) is the active power output by the photovoltaic cell in real time; By controlling the duty cycle α of the unidirectional DC/DC, the photovoltaic cell outputs active power according to P _PV to maintain the stability of the DC bus power. 9. The method for configuring energy storage capacity of a photovoltaic power distribution network according to claim 1, wherein in S4, controlling the second capacity configuration storage bank of the energy storage capacity configuration device comprises: The energy storage capacity configuration device adopts the strategy of superconducting magnetic energy storage system SMES priority regulation and vanadium liquid flow battery energy storage VRB supplementary regulation according to the depth of power drop; when the power drop depth is less than 40%, only SMES charging and discharging is used to maintain power stability, VRB is temporarily not put into operation, and SMES performs reactive power regulation; when the power drop depth is greater than 40%, VRB is put into operation, and VRB performs active power regulation, including: (1) After a power drop fault occurs, an unbalanced power ΔP ₁ is generated between the system input and output:

The unbalanced power ΔP ₁ is decomposed into high-frequency and low-frequency parts _PH1 and _PL1 through the capacity configuration decomposition control strategy; the obtained energy storage power command is distributed to the energy storage capacity configuration device for power regulation, and _PH1 and _PL1 are used as the input reference values of SMES and VRB power feedforward control respectively; (2) When the power drop depth is less than 40%, only the inverter on the SMES side performs the second capacity configuration storage bank control, and the reactive current reference value i _SMEs output by the SMES energy storage is obtained by the following formula:

Where, P _H1 is the SMES power feedforward control input reference value; cosφ is the SMES power factor, which is 0.5; Take i _SMES as the input of the proportional integral controller PI, and then perform pulse width modulation on the output signal of the PI controller through the PWM controller to obtain the reactive power Q _SMES that the SMES energy storage needs to absorb or emit:

Where α is the PWM modulation ratio, X _ac is the AC side incoming line inductance; Through the current inner loop control, α is adjusted to make SMES absorb or emit reactive power to the maximum extent according to Q _SMES ; (3) When the power drop depth is greater than 40%, when both energy storage systems are put into operation, taking into account the capacity constraints of the two energy storage systems, the high- and low-frequency power instructions in step (1) are used to track the energy storage charging and discharging status in real time, and the total margin of the hybrid energy storage system and its own maximum charge and discharge power limit are combined with the real-time SOC size of the energy storage system to allocate power to the two energy storage systems. By dynamically updating the charge and discharge power instructions of the energy storage capacity configuration device, high-quality scheduling tracking is achieved, including: 1) The real-time SOC size of the hybrid energy storage is obtained by the following formula, which are SOC _SMES (t) and SOC _VRB (t):

In the formula,

are the rated capacities of SEMS energy storage and VRB energy storage respectively; t is time; k is a constant coefficient ranging from 1 to 2; 2) The high and low frequency reference power _PH1 , _PL1 obtained by the capacity configuration decomposition control strategy in step (1) and the real-time SOC size of the hybrid energy storage are comprehensively optimized through the following formula to obtain the dispatching power reference instruction of SMES and VRB:

As shown below:

Where P _SP (t) is the system dispatching power, which is the target power curve given by the upper-level power grid operation department; Δt is the working step length, which is 2.5min; T _V is the filtering time constant, which is 26.02; 3) The dispatch power reference instructions of SMES and VRB are obtained

The feedback is respectively fed back to the SMES and VRB inverter control signal input values to realize the dynamic update of the power instructions for the two energy storages, as shown in the following formula:

In the formula,

Updated proportional-integral controller input values for SMES,

Updated proportional-integral controller input values for VRB; SMES updates the reactive current reference value

Perform reactive power control in step (2); VRB then adjusts the power reference value according to the updated power reference value.

Perform active power control as follows: The updated power reference value

As the input of VRB proportional integral controller PI, after being adjusted by the controller, the input quantity α _PWM of the pulse width modulator is calculated using the following formula:

After being adjusted by the pulse width modulator, the VRB battery is charged/discharged according to P _VRB :

In the formula,

They are respectively the active and reactive current reference values of VRB battery. 10. A method system for configuring energy storage capacity of a photovoltaic distribution network according to any one of claims 1 to 6, characterized in that the energy storage capacity configuration system for a photovoltaic distribution network comprises: The system status identification module is used to detect the power U _PCC of the distribution network connection node in real time and to identify the status of the photovoltaic energy storage capacity configuration equipment; A capacity configuration mode division module, used for dividing the capacity configuration mode into two capacity configuration storage repositories according to the state of the photovoltaic energy storage capacity configuration based on the judgment result of the system state judgment module; A first capacity configuration storage repository control module, used for controlling the first capacity configuration storage repository when the power grid connection node power judgment module of the system state judgment module operates normally; The second capacity configuration storage repository control module is used to control the second capacity configuration storage repository of the photovoltaic converter and the energy storage capacity configuration device respectively after a power reduction failure occurs in the power grid connection node power judgment module of the system state judgment module.

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