CN114421526A - A distributed photovoltaic multi-cluster voltage control method, system and storage medium - Google Patents

Abstract

The present invention relates to a distributed photovoltaic multi-cluster voltage control method, system and storage medium, which include: using the cluster division result and the cluster voltage deviation degree of each cluster to preliminarily determine a safe cluster and a dangerous cluster, and carry out an analysis on the dangerous cluster. On-site voltage regulation; if the on-site voltage regulation fails, the reactive power-voltage sensitivity factor between the clusters is calculated, and the safe cluster and the dangerous cluster are re-determined according to the reactive power-voltage sensitivity factor; The safe cluster with the largest sensitivity factor between the leading node and the dangerous cluster leading node makes the inverter in the safe cluster additionally issue the total reactive power ΔQ, and distributes the distributed photovoltaic power sources in the cluster based on the total reactive power Allocate reactive power; cyclically detect the voltage deviation of each cluster, if it is still in a dangerous cluster, re-determine a safe cluster, otherwise, the voltage of each cluster is within the safety margin to achieve grid-level voltage stability control. The invention can be widely applied in the field of voltage control of the distribution network of the new energy power system.

Description

A distributed photovoltaic multi-cluster voltage control method, system and storage medium

technical field

The invention relates to the field of new energy power system distribution network voltage control, in particular to a distributed photovoltaic multi-cluster voltage control method, system and storage medium based on cluster voltage deviation.

Background technique

The clean energy represented by photovoltaics has developed rapidly around the world due to its economical, clean and environmental advantages, which has greatly eased the pressure of fossil energy depletion and ecological environment deterioration. As the penetration rate of distributed photovoltaic power generation in the distribution network continues to increase, problems such as voltage and frequency fluctuations and over-limits caused by the intermittent, random, and large power fluctuations of distributed photovoltaic power supply output become prominent, which greatly affects the operation of the distribution network. bring great challenges. In order to realize the purpose of real-time stability of the distribution network voltage under the new power system, and to lay a theoretical foundation for the safe and stable operation of the power system under the new energy structure, it is necessary to study the stability control after the distributed photovoltaic is connected. Photovoltaic clusters have small inertia, small damping, and rapid response, and the control of cluster voltage stability has become a difficult point. Distributed photovoltaic power inverter control mode and unreasonable parameter settings lead to low PV utilization, poor economy and large grid voltage fluctuations. Therefore, it is urgent to carry out research on the grid-connected reactive power-voltage dynamic switching control technology of distributed photovoltaic power supply clusters under the new situation and the frequency and voltage active support technology of distributed power supply clusters, so as to construct projects with high proportion of new energy access. Provide a basis for decision-making.

In recent years, many literatures have carried out research on the stabilization method of distributed photovoltaics connected to the distribution network. The main concerns include: inverter control mode, coordination with energy storage, changing transformer taps and other methods and their corresponding methods. Improve methods.

At present, the voltage regulation methods for distributed photovoltaic systems mainly include reactive power compensation and active power reduction. In terms of on-site reactive power compensation, the German Institute of Electrical Engineers proposed four reactive power control strategies suitable for distributed photovoltaics: constant reactive power Q control, constant power factor cosφ control, cosφ(P) control based on photovoltaic active output, and Q(U) control based on the voltage amplitude of the grid connection point. However, as a basic method, it has its own advantages and disadvantages. The constant reactive power method cannot participate in grid voltage regulation in time; when the power factor method is large in photovoltaic power generation and on-site load, redundant power transmission will cause a lot of losses; based on the voltage at the grid connection point The control mode has weak voltage regulation ability at the grid connection point. When the output capacity of the inverter reaches the rated capacity and the voltage still exceeds the limit, the active power reduction method is adopted. Aiming at the reactive power regulation capability of photovoltaic inverters, a multi-mode voltage control model for low-voltage distribution networks is established based on the reactive voltage sensitivity matrix. Reactive power; when the network operation is risk-free, the optimization of network loss and power factor is used as the basis for the reactive power adjustment of the inverter, but processing the entire distribution network has a large amount of data, low efficiency and poor real-time performance, which leads to the effect of voltage fluctuation control. not good.

SUMMARY OF THE INVENTION

Aiming at the shortage of the voltage stability problem after the current distributed photovoltaics are connected to the distribution network, the purpose of the present invention is to provide a distributed photovoltaic multi-cluster voltage control method, system and storage medium, which can effectively adapt to adjust the operating voltage of the power grid.

In order to achieve the above object, the present invention adopts the following technical scheme: a distributed photovoltaic multi-cluster voltage control method, which includes: using the cluster division result and the cluster voltage deviation degree of each cluster to preliminarily determine a safe cluster and a dangerous cluster, Dangerous clusters perform on-site voltage regulation; if the on-site voltage regulation fails, calculate the reactive power-voltage sensitivity factor between the clusters, and re-determine the safe cluster and the dangerous cluster according to the reactive power-voltage sensitivity factor; In the safe cluster with the largest sensitivity factor between the leading node in the cluster and the leading node in the dangerous cluster, the inverter in the safe cluster will issue an additional total reactive power ΔQ, and based on the total reactive power, it will be sent to each node in the cluster. Distributed photovoltaic power sources distribute reactive power; cyclically detect the voltage deviation of each cluster, if it is still in a dangerous cluster, re-determine a safe cluster, otherwise, the voltage of each cluster is within the safety margin to achieve grid-level voltage stability control.

Further, using the cluster division result and the cluster voltage deviation degree of each cluster to preliminarily determine the safe cluster and the dangerous cluster includes: using the cluster division result and the cluster voltage deviation degree of each cluster to determine whether the voltage in each cluster exceeds the limit, if If the limit is exceeded, it is a dangerous cluster, otherwise it is a safe cluster.

Further, the on-site voltage regulation of the dangerous cluster includes: scheduling inverters with adjustable reactive power capacity in the dangerous cluster, and switching the inverter to an improved droop control mode for on-site regulation pressure.

Further, the determination of the cluster voltage deviation includes: obtaining each photovoltaic cluster microgrid based on the cluster division result; for each node in the cluster, calculating the reactive voltage sensitivity of each node to the dominant node; The power voltage sensitivity is calculated to obtain the voltage deviation of each cluster.

Further, the voltage deviation is:

In the formula, M _θ is the cluster voltage deviation; N is the number of nodes in the cluster; U _i is the real-time operating voltage of node i, S _iθ is the reactive voltage sensitivity coefficient of node i to the dominant node θ, and U _min is each node in the cluster. The minimum terminal voltage, U _max is the maximum terminal voltage of each node in the cluster.

Further, the total reactive power is:

In the formula, ΔQ _j is the total reactive power generated by PV inverters in the safe cluster; S _ij is the reactive power-voltage sensitivity factor between the leading node j of the safe cluster and the leading node i of the dangerous cluster, and U _min is each node in the cluster The minimum terminal voltage, U _max is the maximum terminal voltage of each node in the cluster, and U _i is the real-time operating voltage of the i node.

Further, allocating reactive power to each distributed photovoltaic power source in the cluster based on the total reactive power includes:

Establish active/reactive voltage sensitivity matrix between clusters and between nodes;

According to the node active/reactive voltage sensitivity matrix, the relationship between the node voltage amplitude change and the power change is obtained, and the difference between the node's real-time voltage and the voltage rating is obtained;

According to the difference between the real-time voltage of the node and the rated value, the PV reactive power variation of each node is calculated, and the reactive power generated by each distributed PV power source in the cluster is obtained from the PV reactive power variation K of each node and the reactive power-voltage sensitivity factor. The total reactive power is distributed to the distributed photovoltaic power sources in the cluster.

A distributed photovoltaic multi-cluster voltage control system, comprising: a primary division module, which uses a cluster division result and a cluster voltage deviation degree of each cluster to preliminarily determine a safe cluster and a dangerous cluster, and performs on-site voltage regulation on the dangerous cluster; The cluster determination module, in which the on-site voltage regulation fails, calculates the reactive power-voltage sensitivity factor between the clusters, and re-determines the safe cluster and the dangerous cluster according to the reactive power-voltage sensitivity factor; the power distribution module selects each cluster. In the safe cluster with the largest sensitivity factor between the leading node in the cluster and the leading node in the dangerous cluster, the inverter in the safe cluster will issue an additional total reactive power ΔQ, and based on the total reactive power, it will be sent to each node in the cluster. The distributed photovoltaic power source distributes reactive power; the detection module cyclically detects the voltage deviation of each cluster. If it is still in a dangerous cluster, the safety cluster is re-determined. Otherwise, the voltage of each cluster is within the safety margin to achieve grid-level voltage stability. control.

A computer-readable storage medium storing one or more programs comprising instructions that, when executed by a computing device, cause the computing device to perform any of the methods as claimed in the preceding claims method.

A computing device comprising: one or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the The one or more programs include instructions for performing any of the above-described methods.

The present invention has the following advantages due to taking the above technical solutions:

Based on voltage and current double closed-loop control, the invention adopts improved droop control and PQ control mode switching for grid-connected inverters, and establishes a distributed photovoltaic power supply access distribution network model. Then use the cluster division result and the voltage deviation level index of each cluster to evaluate the risk of each cluster voltage exceeding the limit, and establish the reactive power voltage sensitivity matrix between each cluster and each node. Finally, the voltage adaptive control mode is adopted for the distributed photovoltaic inverters in each cluster to achieve grid voltage stability, which can effectively adapt to adjust the operating voltage of the grid.

Description of drawings

FIG. 1 is a schematic diagram of a voltage control method for distributed photovoltaic multi-clusters in an embodiment of the present invention;

2 is an equivalent circuit diagram of a photovoltaic power supply in an embodiment of the present invention;

3 is a grid-connected diagram of a photovoltaic power source in an embodiment of the present invention;

4 is a control block diagram of a droop control inverter in an embodiment of the present invention;

5 is a distributed photovoltaic access IEEE33 node simulation system in an embodiment of the present invention;

6 is a schematic diagram of a system voltage level of an IEEE33 node in an embodiment of the present invention;

7a is a schematic diagram of distributed photovoltaic active output in PQ mode according to an embodiment of the present invention;

7b is a schematic diagram of distributed photovoltaic reactive power output in PQ mode according to an embodiment of the present invention;

FIG. 7c is a graph of distributed photovoltaic voltage variation in Q(U) mode according to an embodiment of the present invention;

FIG. 7d is a variation diagram of distributed photovoltaic reactive power in Q(U) mode according to an embodiment of the present invention;

Fig. 8 is the reactive power and voltage sensitivity relation diagram of the improved IEEE33 node system in an embodiment of the present invention;

FIG. 9 is a graph of voltage changes of IEEE33 nodes before and after a regulation mode based on cluster voltage deviation according to an embodiment of the present invention.

Detailed ways

To make the objectives, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are some, but not all, embodiments of the present invention. Based on the described embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art fall within the protection scope of the present invention.

It should be noted that the terminology used herein is for the purpose of describing specific embodiments only, and is not intended to limit the exemplary embodiments according to the present application. As used herein, unless the context clearly dictates otherwise, the singular is intended to include the plural as well, furthermore, it is to be understood that when the terms "comprising" and/or "including" are used in this specification, it indicates that There are features, steps, operations, devices, components and/or combinations thereof.

The present invention provides a distributed photovoltaic multi-cluster voltage control method, system and storage medium, which include: dividing a distribution network actually containing distributed photovoltaics into clusters according to an improved electrical distance, and setting the grid-connected inverter control mode to a possible Automatic switching according to cluster voltage deviation. According to the cluster voltage deviation degree of each cluster, the voltage out-of-limit level of each cluster is evaluated, and the dominant node of the cluster is selected and the sensitivity relationship between the dominant nodes is calculated based on the establishment of the reactive voltage sensitivity matrix between each cluster and each node. Finally, the control mode based on cluster voltage deviation is used to coordinate and cooperate with each safety cluster and dangerous cluster to achieve grid voltage stability. The method avoids the increased workload caused by processing a large amount of data of each node of the distribution network and reduces the real-time effectiveness of voltage control, and has stronger pertinence and adaptability, so that the grid voltage can be more quickly stabilized within a safe range.

Aiming at the distribution network with high proportion of distributed photovoltaics, the present invention uses the electrical distance based on impedance as the grouping index to group the distribution network with distributed photovoltaics, calculates the voltage deviation of each cluster, and adopts the method for clusters with serious limit violations. Based on the improved droop control of virtual impedance, the reactive power in each safe running cluster is adjusted to adjust the voltage of each cluster in the power grid. The method simplifies the voltage control of the distribution network, avoids the control of each node, and greatly increases the complexity of processing data and is not easy to operate. At the same time, the multi-level voltage control is realized by grouping the distribution network connected by a high proportion of photovoltaics, so that the control method adopted by the present invention can track the operation characteristics of the power grid in real time and adopt a corresponding control mode to maintain the stability of the power grid voltage.

In one embodiment of the present invention, a distributed photovoltaic multi-cluster voltage control method is provided. In this embodiment, as shown in Figure 1, the method includes the following steps:

1) Use the cluster division result and the cluster voltage deviation degree of each cluster to preliminarily determine the safe cluster and the dangerous cluster, and adjust the voltage of the dangerous cluster on the spot;

2) If the local voltage regulation fails, calculate the reactive power-voltage sensitivity factor between each cluster, and re-determine the safe cluster and the dangerous cluster according to the reactive power-voltage sensitivity factor;

3) Select the safety cluster with the largest sensitivity factor between the leading node in each cluster and the leading node of the dangerous cluster, so that the inverters in the safe cluster additionally issue a total reactive power △Q, and based on the total reactive power Distributed photovoltaic power sources distribute reactive power;

4) Circularly detect the voltage deviation of each cluster. If it is still in a dangerous cluster, re-determine the safe cluster. Otherwise, the voltage of each cluster is within the safety margin to achieve grid-level voltage stability control.

In this embodiment, a distributed photovoltaic power supply access distribution network model needs to be established. First, the photovoltaic power supply side model is established. As shown in Figure 2, the output current I of the photovoltaic power supply is:

where I _SC is the short-circuit current of the photovoltaic cell, I _d is the diode saturation current, I _Sh is the leakage current of the photovoltaic cell, I ₀ is the reverse saturation current, R _S is the series equivalent resistance, R _sh is the parallel equivalent resistance, U Output voltage for photovoltaic power supply.

Considering the practicality of the project, a practical mathematical model of the photovoltaic power supply is established. At this time, the output current I of the photovoltaic power supply is:

Among them, U is the output voltage of photovoltaic power supply, C ₁ is the current proportional coefficient, C ₂ is the current index coefficient; U _oc is the open circuit voltage, U _m is the maximum power voltage, and I _m is the maximum power current. The active power P of the PV power supply output (load absorption) is:

Among them, R ₁ is the load resistance, X ₁ is the load impedance, R ₀ is the internal resistance of the power supply, and X ₀ is the internal impedance of the power supply.

Then when X ₀ +X ₁ =0, the power can have a maximum value, which can be substituted into formula (1-5) and derived:

需要注意的是Z₀上同样消耗了相同数值的功率，最大功率传输效率为50％， Z₀为电源阻抗。采用干扰观测法等方法可实现最大功率点跟踪控制。Therefore, the condition for the load to obtain the maximum power is that R ₁ =R ₀ , X ₁ =-X ₀ . At this time, the maximum active power consumed by the load Z _L is

It should be noted that Z ₀ also consumes the same amount of power, the maximum power transfer efficiency is 50%, and Z ₀ is the power supply impedance. The maximum power point tracking control can be realized by methods such as interference observation method.

Then a photovoltaic grid-connected model is established. As shown in Figure 3, the photovoltaic grid-connected inverter is connected to the grid and passes through the filter inductor and capacitor. The voltage equation of the filter inductor L _m is:

为初相角，i为相位系数。忽略逆变器所接滤波电阻R_m(其值很小)，则滤波电容电流方程可写为：where m is the controllable sinusoidal modulation signal, I _pv is the inverter output current, _VL is the load voltage vector, k is the voltage modulation coefficient, V _pv is the inverter output voltage, and ω is the angular frequency of the three-phase electrical quantity size, t is the running time,

is the initial phase angle, and i is the phase coefficient. Ignoring the filter resistance R _m connected to the inverter (its value is very small), the current equation of the filter capacitor can be written as:

Among them, C _m is the size of the filter capacitor, _IL is the size of the current flowing to the load, and I _Pcc is the size of the current flowing to the grid-connected point.

The outer loop control is a voltage loop, combined with PI control to achieve the function of stabilizing the load voltage to a given voltage, and the inner loop control is a current loop to improve the dynamic response capability of the system.

When the photovoltaic power grid-connected model is three-phase symmetrical, the transfer function of the filter output load voltage vector (load-side voltage) _VL and the inverter output voltage V _pv is shown in equation (1-10).

In the formula,

After considering that the distributed photovoltaic is connected to the distribution network, when the photovoltaic adopts unit power factor control and the active power output is much larger than the local load, and the reactive power loss is ignored, the grid voltage is set as V _PCC , there are:

In the formula, P _pv represents the active power output by the inverter, and X represents the system equivalent reactance.

If you want to keep the voltage of the grid connection point unchanged before and after connecting to the photovoltaic, ignoring the vertical axis voltage difference increment, the required reactive power Q _PV size is:

In the formula, _{QL represents the reactive power of the load, and PL represents} the active power of the load.

In the above step 1), using the cluster division result and the cluster voltage deviation degree of each cluster to preliminarily determine the safe cluster and the dangerous cluster, specifically: using the cluster division result and the cluster voltage deviation degree of each cluster to determine whether the voltage in each cluster exceeds the limit, If the limit is exceeded, it is a dangerous cluster, otherwise it is a safe cluster.

Among them, on-site voltage regulation for dangerous clusters: dispatching inverters with adjustable reactive power capacity in dangerous clusters, and switching the inverters to improved droop control mode for on-site voltage regulation.

In this embodiment, in the inverter control, the basic control principle of Q(U) is shown in Figure 4. When the photovoltaic grid is connected with a voltage source inverter topology, the inverter is calculated based on the abc three-phase static coordinate system. The output active power P and reactive power Q are:

Among them, θ _i is the impedance power factor angle between the inverter and the grid-connected point, α is the voltage phase angle difference between the inverter output and the grid-connected point, Z _m is the line impedance, U _pv is the inverter terminal voltage, U _pcc is the grid connection point voltage.

Taking two distributed photovoltaic grid-connected inverters in parallel as an example, when the line impedance Z _m is mainly inductive:

The phase angle is obtained after frequency integration, namely:

Among them, f _σ is the rated frequency, α _σ is the rated power angle, X _m is the load reactance, and t0 is the end time of the integral calculation.

The corresponding droop control expression is:

Among them, P _m is the PV measured output active power, f is the PV measured frequency, f ^σ is the PV rated frequency, K _P is the active power droop coefficient, K _q is the reactive power droop coefficient, and U ^σ is the PV rated output voltage.

Perform Parker transformation on the real-time measurement of the three-phase voltage and current of the distributed photovoltaic grid-connected inverter terminal, to obtain the dq axis components of the voltage and current respectively, and realize the power decoupling calculation. The Parker transformation matrix T _abc/dq is:

Where ω is the angular frequency of the three-phase electrical quantity. After the three-phase voltage and current undergo Parker transformation, the dq-axis components are obtained as _umd , _umq , _imd , and _imq , respectively. Calculate the output power of the inverter at this time:

p=u _md i _md +u _mq i _mq (1-21)

q=u _mq i _md -u _md i _mq (1-22)

Using grid voltage oriented vector control, the output side current of the photovoltaic grid-connected inverter, the d-axis of the synchronous rotating coordinate system and the grid voltage vector are rotated synchronously, and the d-axis of the synchronous rotating coordinate system is in the same direction as the grid voltage vector, then the power decoupling is realized. , and on this basis, the inverter PQ control and droop control strategies are implemented.

After the instantaneous power output of the inverter is measured, because the high-frequency components change rapidly and the amplitude is generally small, it will cause unnecessary frequent actions of the controller and reduce its service life. Therefore, it is necessary to remove its high-frequency components through a low-pass filter to enhance the system. stability:

where _ωσ is the cutoff frequency of the low-pass filter.

比即满足式(1-25)、(1-26)：For a distributed photovoltaic cluster with droop control, the internal power should be allocated according to the capacity to prevent the inverter from being overloaded and damaged, causing further voltage fluctuations or even exceeding the limit. When the system is in a stable operation state, the operating frequency of each unit in the cluster is the same, that is, ω ₁ = ω ₂ , so according to equations (1-15) and (1-18), it is only necessary that all inverters in the cluster have the same reference frequency under the rated active power, and the droop coefficients (K _1P , K _2P ) are constant power

The ratio satisfies equations (1-25) and (1-26):

ω ₁ ^σ = ω ₂ ^σ (1-25)

At this time, the active power output of the inverter can be equally divided according to the rated power within the cluster:

K _1P P _1m = K _2P P _2m (1-27)

According to formulas (1-16) and (1-19), it can be known that under the premise that (1-28) and (1-29) are established, it is necessary to realize the distribution of reactive power according to the capacity, that is, the premise of (1-30) is established. is the capacity E ₁ =E ₂ .

U ₁ ^σ = U ₂ ^σ (1-28)

At this time, the reactive power output of the inverter can be equally divided according to the rated power within the cluster:

K _1q Q _1m = K _2q Q _2m (1-30)

The slope of the reactive voltage droop control curve is generally small, and a small disturbance deviation between the voltages will lead to a large reactive power difference, which will cause inverter overcurrent. When (1-28) and (1-29) are established, the voltage difference between distributed photovoltaics in the cluster is:

ΔU=U ₂ -U ₁ =K _2q Q _2m -K _1q Q _1m (1-31)

Substitute equation (1-19) into equation (1-16) to get

Substitute equation (1-32) into equation (1-31) to get

It can be obtained from the final derivation formula (1-33), on the premise that (1-28) and (1-29) are established, only when the reactive voltage droop coefficient control of distributed photovoltaic inverters in the cluster is inversely proportional to the impedance can Guarantee U ₂ =U ₁ , and then realize that the reactive power is equally divided according to the capacity within the cluster.

The improved droop control coefficient range determination method adopted in this embodiment is: considering the virtual impedance of distributed photovoltaic access to realize power distribution according to capacity. The internal droop coefficient ratio of the distributed photovoltaic cluster is determined. In order to select the appropriate size, the reactive power droop control coefficient is derived:

Suppose there are N nodes and b branches in the cluster, E _vir , E ^σ , P, Q, _PL , _QL , and U are the virtual grid-connected voltage, the rated reference voltage, and the distributed photovoltaic/energy storage output of each node. active power, reactive power of distributed photovoltaic output of each node, active load, reactive load, voltage matrix of each node, E ₀ is the rated voltage matrix, R _m , X _m , K _q are virtual resistance, virtual reactance, Reactive power droop coefficient n×n diagonal matrix, U _b , P _b , Q _b are line voltage drop, transmission active power, and transmission reactive power matrix, respectively. R _b , X _b are the line resistance and reactance matrix, and M is the nodal correlation matrix.

Among them, Q' is the reactive power output of each distributed PV when the reactive power is allocated according to the capacity within the cluster. The virtual output voltage of each distributed photovoltaic power source is:

E _vir =E ^σ -K _q Q (1-34)

The terminal voltage of each node in the cluster is:

The voltage drop on the branch is:

From Kirchhoff's current law, there are:

U _b =M ^T U (1-37)

The power flow balance equation of each node is as follows:

P _b =M ^T (PP _L ) (1-38)

Q _b = M ^T (QQ _L ) (1-39)

By formula (1-34) - formula (1-39) can be obtained:

[M(E ₀ K _q +X _m )+X _b M ^T ]Q=E ₀ M ^T E ^σ -(M ^T R _m +R _b M ^T )P+R _b M ^T P _L +X _b M ^T Q _L (1-40)

According to the previous analysis, the active power can be allocated according to the capacity, as follows:

P=KE _1×n P _L (1-41)

And because in general, the proportion of active power and reactive power of distributed power generation is the same, there are:

Q' ₌ KE _1×n QL (1-43)

The reactive power matrix equation when the grid is actually running is:

Q=Q'+ΔQ (1-44)

Q _L Q=Q'+ΔQ _L (1-45)

Also due to:

The formula (1-40) can be expressed as:

[M(E ₀ K _q +X _m )+X _b M ^T ]Q

=(M ^T X _m +X _b M ^T )Q'-[(M ^T R _m +R _b M ^T )KE _1×n -R _b M ^T ]P _L +X _b M ^T Q _L (1-47 )

The selection range of the droop coefficient can be determined by substituting into the system parameters of the microgrid cluster by formulas (1-43)-(1-47).

In the above step 1), the determination of the cluster voltage deviation includes the following steps:

1.1) Based on the cluster division results, each photovoltaic cluster microgrid is obtained;

1.2) For each node in the cluster, calculate the reactive voltage sensitivity of each node to the dominant node;

1.3) Calculate the voltage deviation of each cluster according to the number of nodes in the cluster and the reactive voltage sensitivity.

Among them, the voltage deviation is:

In the formula, M _θ is the cluster voltage deviation; N is the number of nodes in the cluster; U _i is the real-time operating voltage of node i, S _iθ is the reactive voltage sensitivity coefficient of node i to the dominant node θ, and U _min is each node in the cluster. The minimum terminal voltage, U _max is the maximum terminal voltage of each node in the cluster.

In this embodiment, the reactive power and voltage sensitivity relationship between clusters and between nodes is calculated, and the voltages of all nodes in the cluster are input into the cluster control system to obtain the voltage deviation of each cluster, thereby obtaining the operation of each cluster. Control mode and system parameters in corresponding mode.

In the above step 1.1), the cluster division method includes the following steps:

Determining Modularity Indicators: The strength of the cluster structure is usually explained by the external characteristics of the cluster, such as the degree of internal correlation, the degree of correlation between clusters, the number of clusters, the scale of cluster size, and the rationality of cluster logic. Modularity metrics can quantitatively describe the external characteristics of a community. The modularity metric quantifies the structural strength of the community and determines the optimal number of partitions between each partition and is defined as follows:

In the formula, A _ij represents the weight of the edge between node i and node j, and ∑ _j A _ij is the sum of the weights of all edges connected to node i. If node i and node j are assigned to the same cluster, then δ(i, j) The value is 1, otherwise it is 0. The level of modularity close to 1 reflects the closeness of the connection between nodes in the cluster.

Determining the electrical distance: The electrical relationship of nodes is more significant than the spatial distance. Therefore, the electrical distance is selected as the computational modularity index of the weighted adjacency matrix, and at the same time, the structural performance of the cluster and the strength of the electrical connection are measured. In engineering practice, in order to simplify the method of obtaining the electrical distance, the node impedance matrix is often used to represent the electrical distance matrix. In the cluster division method mentioned in the present invention, the electrical distance between the grounding points is still represented by an impedance matrix, but the two-port network input impedance Z _ij ′ is used to represent the electrical distance of the non-grounding point:

Z _ij ′=Z _ii +Z _jj -2Z _ij (2-2)

In the above step 1.2), the dominant node is: selecting the dominant node of the cluster is mainly based on the monitoring and control of the node voltage. That is to say, the selected cluster dominant nodes must be both observable and controllable. According to the characteristics of the dominant node of the cluster, calculate the comprehensive sensitivity S of all nodes in the distributed power cluster, and the largest S value is the dominant node:

maxS=max(V+dC) (2-4)

Where V represents the observability of the node, C represents the controllability of the node, and d is the weight coefficient.

为节点j对节点i的节点电压灵敏度，n为集群内接有分布式光伏/储能设备的可控节点集合，

为节点i电压幅值相对于节点 j注入无功功率的无功电压灵敏度。where N is the set of all nodes in the cluster,

is the node voltage sensitivity of node j to node i, n is the set of controllable nodes connected with distributed photovoltaic/storage equipment in the cluster,

Reactive voltage sensitivity for node i voltage amplitude relative to node j injected reactive power.

In above-mentioned step 3), total reactive power is:

In the formula, ΔQ _j is the total reactive power generated by PV inverters in the safe cluster; S _ij is the reactive power-voltage sensitivity factor between the leading node j of the safe cluster and the leading node i of the dangerous cluster, and U _min is each node in the cluster The minimum terminal voltage, U _max is the maximum terminal voltage of each node in the cluster, and U _i is the real-time operating voltage of the i node.

In the above step 3), allocating reactive power to each distributed photovoltaic power source in the cluster based on the total reactive power includes the following steps:

3.1) Establish active/reactive voltage sensitivity matrix between clusters and between nodes;

In this embodiment, from the power system load flow Jacobian matrix, the power flow calculation in the distribution network satisfies the following equation:

The matrix transformation of the above formula is:

The active/reactive voltage sensitivity matrix is:

3.2) According to the node active/reactive voltage sensitivity matrix, the relationship between the node voltage amplitude change and the power change is obtained, and the difference ΔU between the node's real-time voltage and the voltage rating is obtained;

In this embodiment, according to the node active/reactive voltage sensitivity matrix, when n nodes in the cluster contain distributed photovoltaics/energy storage, the relationship matrix between the node voltage amplitude change and power change is:

ΔU=S _UP ΔP+S _UQ ΔQ (3-5)

The voltage Vi of each node in the cluster is not only affected by its own power change, but also by the active power and reactive power injected by other nodes:

3.3) Calculate the PV reactive power variation of each node according to the difference between the real-time voltage of the node and the rated value, and obtain the PV reactive power variation K of each node and the reactive power-voltage sensitivity factor to obtain the output voltage of each distributed PV power source in the cluster. Reactive power, to realize the distribution of total reactive power to each distributed photovoltaic power source in the cluster.

In this embodiment, it can be seen from equation (3-1) that changing the distributed photovoltaic output reactive power changes the voltage of the cluster or other clusters, and the change of the output power of the distributed photovoltaic connected to different locations affects the voltage amplitude change at the same point Sizes vary. In order to calculate the PV reactive power variation K of each node, it is necessary to reasonably allocate its power according to the reactive voltage sensitivity relationship of each node in the cluster. It is known that the difference between the real-time voltage of node a and the rated value is ΔU:

为无功-电压灵敏度系数。in,

is the reactive power-voltage sensitivity coefficient.

Then the reactive power emitted by each distributed photovoltaic power source in the computing cluster is:

where ε _i is a Boolean quantity, when the node i in the cluster is connected to the distributed photovoltaic power supply and has adjustable power, its value is 1, otherwise it is 0.

Example:

MATLAB/Simulink is used to build the IEEE33 node with a high proportion of distributed photovoltaic distribution network model as shown in the figure, and the unit models are the same, as shown in Figure 5. The distributed photovoltaic is connected to the distribution network through a transformer (311V/12.66kV), where node 1 is the grid connection point where the distribution network is connected to the large power grid.

Clusters and nodes are defined as follows: the nodes considered in this embodiment are the respective busbars of the distribution network, and the nodes in the calculation example are 33 busbars in the IEEE33 nodes. In addition, the cluster in this embodiment specifically refers to the presence of distributed photovoltaics. The connected distribution network is each cluster microgrid after the cluster is divided, and each cluster in the calculation example is each microgrid system composed of multiple nodes in the dotted box in Figure 5.

Using the electrical distance clustering algorithm, the clustering results based on the IEEE33 node distribution network system partition are shown in Table 1.

Table 1 Grouping results

When the photovoltaic system is not connected, if the voltage of the grid connection point is set to the rated voltage of 12.66KV, the IEEE33 node voltage diagram as shown in Figure 6 is obtained.

Build a grid-connected model of distributed photovoltaic power supply via inverter, including photovoltaic power supply with PQ power decoupling control and photovoltaic power supply model with improved droop control suitable for grid-connected point voltage. The former sets the irradiance unchanged in a short period of time, that is, P remains unchanged, and changing the reactive power enables distributed photovoltaics to participate in voltage regulation between clusters and/or within clusters. The latter is set to increase the voltage of the grid connection point at the moment of 0.02s.

As shown in Figure 7a to Figure 7d, it can be seen that in the power decoupling control mode, when the active output is unchanged, the reactive output size is independently changed to participate in the voltage regulation, the active output size is not affected, and the decoupling control, Q(U) control is realized. In the mode, when the voltage of the monitoring point increases, the output reactive power is automatically reduced to participate in the voltage regulation, which can reduce the voltage fluctuation and effectively adjust the local voltage close to the rated voltage.

Calculate the voltage change of other nodes caused by the unit reactive power change of a node, that is, the reactive voltage sensitivity, and generate the sensitivity factor graph as shown in Figure 8. The x-axis is the unit reactive power change node, the y-axis is the voltage change node, and the z-axis is the change unit. The per-unit value of the corresponding node voltage increase after reactive power.

Through calculation, the control modes adopted according to the cluster voltage deviation for clusters with distributed photovoltaics are as follows: including 20, 22 connected photovoltaic clusters 5, the cluster voltage deviation is within the stability margin, and the cluster voltage deviation is 0.005348 , PQ control can be used to participate in grid voltage regulation, and the photovoltaics connected to nodes 20 and 22 in cluster 5 still have reactive power margins. From the reactive voltage sensitivity relationship of each cluster, it can be seen that when nodes 20 and 22 generate additional reactive power, cluster 3 is at risk. , 4, 7 The voltage increases to verify the rationality of coordination between clusters. Other security clusters can participate in grid-level voltage regulation in the same way.

The PV cluster 7 with 31 nodes has a large voltage deviation, and the cluster voltage deviation is 0.0533. The improved droop control based on virtual impedance is adopted, and the photovoltaics in the cluster participate in the voltage regulation. The PV cluster 3 with 14 and 16 nodes has a large voltage deviation, and the cluster voltage deviation is 0.0606. The improved droop control based on virtual impedance is adopted, and the PV participates in voltage regulation. The 18-node photovoltaic cluster 4 has a large voltage deviation, and the cluster voltage deviation is 0.0647. The improved droop control based on virtual impedance is adopted, and the photovoltaic participates in voltage regulation. Compared with the cluster-based PQ control methods, the system voltage before and after optimization of each method is shown in Figure 9.

It can be seen from Figure 9 that under the conventional PQ control method, cluster 3 still exceeds the limit, and the voltage deviation is 0.0506. However, the cluster voltage control method proposed in this paper makes the distribution network voltage recovery level obvious, and each cluster recovers to a safe level after calculation. Within the level of the voltage deviation degree of 2, it is reduced to below 0.05, indicating that it has a good voltage regulation ability, which verifies the rationality of the voltage regulation control method based on the cluster voltage deviation degree proposed in this paper.

When the number of nodes in the distribution network is complex, the single grid level control needs to process huge data, which is difficult to meet the real-time control requirements and the data processing efficiency is low, and it is difficult to achieve the required control effect. It is difficult to maximize the coordination and cooperation of the voltage of each node. Therefore, the cluster level as a comprehensive method has significantly improved the voltage control effect. First, the actual distribution network with distributed photovoltaics is clustered according to the improved electrical distance. The control mode of the grid-connected inverter is set to automatically switch according to the voltage over-limit level. Then, the voltage over-limit level of each cluster is evaluated according to the cluster voltage deviation index of each cluster, and the dominant node of each cluster is selected based on the reactive voltage sensitivity matrix between each node and the voltage sensitivity relationship between the clusters is calculated. Finally, the voltage control mode based on the cluster voltage deviation is adopted for the distributed photovoltaic inverters in each cluster to achieve grid voltage stability. Among them, the cluster voltage deviation degree voltage control mode is: when the voltage deviation degree of a cluster exceeds the set threshold, it is a dangerous cluster, and the cluster preferentially adopts the improved Q(U) mode on-site voltage control; other voltage deviation degrees In the safety cluster within the threshold safety range, select the safety cluster with the largest sensitivity factor between the leading node in each cluster and the leading node of the dangerous cluster, make the inverter in the safety cluster issue additional △Q, and then return to determine whether the dangerous cluster has entered. Security domain, if not, select a security cluster to cooperate with voltage regulation. The reactive power allocation criterion in the safety cluster is that the inverters with adjustable reactive power capacity are allocated proportionally according to the size of the sensitivity factor. The method simplifies the grid voltage control, avoids the increased workload caused by processing a large amount of data of each node of the distribution network, and reduces the real-time effectiveness of the voltage control. At the same time, by using different control modes for each cluster, it has stronger pertinence and adaptability, and considers the coordinated control between clusters, so that the grid voltage can be more quickly stabilized within a safe range.

In summary, the present invention is based on voltage and current double closed-loop control, adopts improved droop control and PQ control mode switching for grid-connected inverters, and establishes a distributed photovoltaic power supply access distribution network model. Then use the cluster division result and the voltage deviation level index of each cluster to evaluate the risk of each cluster voltage exceeding the limit, and establish the reactive power voltage sensitivity matrix between each cluster and each node. Finally, the voltage adaptive control mode is adopted for the distributed photovoltaic inverters in each cluster to achieve grid voltage stability. Through numerical example simulation, the results show that the adopted cluster voltage support method can effectively adapt to adjust the operating voltage of the power grid, thus verifying the effectiveness of the method.

In one embodiment of the present invention, a distributed photovoltaic multi-cluster voltage control system is provided, which includes:

The primary division module uses the cluster division result and the cluster voltage deviation of each cluster to preliminarily determine the safe cluster and the dangerous cluster, and adjust the voltage of the dangerous cluster on the spot;

In the cluster determination module, if the local voltage regulation fails, the reactive power-voltage sensitivity factor between each cluster is calculated, and the safe and dangerous clusters are re-determined according to the reactive power-voltage sensitivity factor;

The power distribution module selects the safety cluster with the largest sensitivity factor between the leading node in each cluster and the leading node of the dangerous cluster, so that the inverters in the safety cluster additionally issue the total reactive power △Q, and distribute the total reactive power to the cluster based on the total reactive power. Distributed reactive power of each distributed photovoltaic power source;

The detection module cyclically detects the voltage deviation of each cluster. If it is still in a dangerous cluster, the safety cluster is re-determined. Otherwise, the voltage of each cluster is within the safety margin to achieve grid-level voltage stability control.

The system provided in this embodiment is used to execute the foregoing method embodiments. For specific processes and details, please refer to the foregoing embodiments, which will not be repeated here.

An embodiment of the present invention provides a computing device structure. The computing device may be a terminal, which may include: a processor, a communications interface, a memory, a display screen, and an input device. Among them, the processor, the communication interface and the memory complete the communication with each other through the communication bus. The processor is used to provide computing and control capabilities. The memory includes a non-volatile storage medium and an internal memory, the non-volatile storage medium stores an operating system and a computer program, the computer program is executed by the processor to implement a control method; the internal memory is non-volatile The operating system and computer program in the storage medium provide an environment for execution. The communication interface is used for wired or wireless communication with an external terminal, and the wireless communication can be realized by WIFI, a management network, NFC (Near Field Communication) or other technologies. The display screen may be a liquid crystal display screen or an electronic ink display screen, and the input device may be a touch layer covered on the display screen, a button, a trackball or a touchpad set on the casing of the computing device, or an external Keyboard, trackpad or mouse, etc. The processor can call the logic instructions in the memory to perform the following method: use the cluster division result and the cluster voltage deviation degree of each cluster to preliminarily determine the safe cluster and the dangerous cluster, and perform local voltage regulation on the dangerous cluster; , then calculate the reactive power-voltage sensitivity factor between each cluster, and re-determine the safe cluster and the dangerous cluster according to the reactive power-voltage sensitivity factor; select the safe cluster with the largest sensitivity factor between the leading node in each cluster and the leading node of the dangerous cluster, Increase the total reactive power △Q of the inverters in the safe cluster, and distribute reactive power to each distributed photovoltaic power source in the cluster based on the total reactive power; cyclically detect the voltage deviation of each cluster, if it is still in a dangerous cluster, Then, the safety cluster is re-determined. Otherwise, the voltage of each cluster is within the safety margin, and the grid-level voltage stability control is realized.

In addition, the above-mentioned logic instructions in the memory can be implemented in the form of software functional units and can be stored in a computer-readable storage medium when sold or used as an independent product. Based on this understanding, the technical solution of the present invention can be embodied in the form of a software product in essence, or the part that contributes to the prior art or the part of the technical solution. The computer software product is stored in a storage medium, including Several instructions are used to cause a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, Read-Only Memory (ROM, Read-Only Memory), Random Access Memory (RAM, Random Access Memory), magnetic disk or optical disk and other media that can store program codes .

Those skilled in the art can understand that the structure of the above-mentioned computer equipment is only a partial structure related to the solution of the present application, and does not constitute a limitation on the computing device to which the solution of the present application is applied, and the specific computing device may include more or Fewer components, or some components are combined, or have a different arrangement of components.

In one embodiment of the present invention, there is provided a computer program product comprising a computer program stored on a non-transitory computer-readable storage medium, the computer program comprising program instructions, when the program instructions When executed by a computer, the computer can execute the methods provided by the above method embodiments, for example, including: using the cluster division result and the cluster voltage deviation degree of each cluster to preliminarily determine a safe cluster and a dangerous cluster, and perform on-site voltage regulation on the dangerous cluster ; If the local voltage regulation fails, calculate the reactive power-voltage sensitivity factor between each cluster, and re-determine the safe cluster and the dangerous cluster according to the reactive power-voltage sensitivity factor; select the sensitivity between the leading node in each cluster and the leading node of the dangerous cluster The safety cluster with the largest factor makes the inverters in the safety cluster additionally generate total reactive power △Q, and distribute reactive power to each distributed photovoltaic power source in the cluster based on the total reactive power; cyclically detect the voltage deviation of each cluster, If it is still in a dangerous cluster, the safety cluster is re-determined. Otherwise, the voltage of each cluster is within the safety margin, and the grid-level voltage stability control is realized.

In one embodiment of the present invention, a non-transitory computer-readable storage medium is provided, where the non-transitory computer-readable storage medium stores server instructions, the computer instructions cause a computer to execute the methods provided in the above embodiments, for example, including : Use the cluster division result and the cluster voltage deviation of each cluster to preliminarily determine the safe cluster and the dangerous cluster, and perform local voltage regulation on the dangerous cluster; if the local voltage regulation fails, calculate the reactive power-voltage sensitivity factor between the clusters, Re-determine the safe cluster and the dangerous cluster according to the reactive power-voltage sensitivity factor; select the safe cluster with the largest sensitivity factor between the leading node in each cluster and the leading node of the dangerous cluster, so that the inverters in the safe cluster will issue additional total reactive power △ Q, and distribute reactive power to each distributed photovoltaic power source in the cluster based on the total reactive power; cyclically detect the voltage deviation of each cluster, if it is still in a dangerous cluster, re-determine the safe cluster, otherwise, the voltage of each cluster is within the safety margin It can realize grid-level voltage stability control within the range.

The implementation principle and technical effect of the computer-readable storage medium provided by the above-mentioned embodiments are similar to those of the above-mentioned method embodiments, and details are not described herein again.

The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the present application. It will be understood that each flow and/or block in the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to the processor of a general purpose computer, special purpose computer, embedded processor or other programmable data processing device to produce a machine such that the instructions executed by the processor of the computer or other programmable data processing device produce Means for implementing the functions specified in a flow or flow of a flowchart and/or a block or blocks of a block diagram.

These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory result in an article of manufacture comprising instruction means, the instructions The apparatus implements the functions specified in the flow or flow of the flowcharts and/or the block or blocks of the block diagrams.

These computer program instructions can also be loaded on a computer or other programmable data processing device to cause a series of operational steps to be performed on the computer or other programmable device to produce a computer-implemented process such that The instructions provide steps for implementing the functions specified in the flow or blocks of the flowcharts and/or the block or blocks of the block diagrams.

Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present invention, but not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand: it can still be Modifications are made to the technical solutions described in the foregoing embodiments, or some technical features thereof are equivalently replaced; and these modifications or replacements do not make the essence of the corresponding technical solutions depart from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims (10)

1. A distributed photovoltaic multi-cluster voltage control method is characterized by comprising the following steps:

preliminarily determining a safety cluster and a dangerous cluster by using cluster division results and cluster voltage deviation degrees of the clusters, and carrying out local voltage regulation on the dangerous cluster;

if the local voltage regulation fails, calculating reactive-voltage sensitivity factors among the clusters, and re-determining a safe cluster and a dangerous cluster according to the reactive-voltage sensitivity factors;

selecting a safety cluster with the maximum sensitivity factor between the main guide node and the dangerous cluster main guide node in each cluster, enabling an inverter in the safety cluster to increase the total reactive power quantity delta Q, and distributing reactive power to each distributed photovoltaic power supply in the cluster based on the total reactive power quantity;

and circularly detecting the voltage deviation degree of each cluster, re-determining the safe cluster if the voltage deviation degree of each cluster is still in a dangerous cluster, and otherwise, controlling the voltage stability of the power grid level if the voltage deviation degree of each cluster is in a safety margin.

2. The distributed photovoltaic multi-cluster voltage control method of claim 1, wherein the preliminary determination of the safety cluster and the danger cluster by using the cluster division result and the cluster voltage deviation degree of each cluster comprises: and judging whether the voltage in each cluster exceeds the limit or not by utilizing the cluster division result and the cluster voltage deviation degree of each cluster, wherein if the voltage in each cluster exceeds the limit, the cluster is a dangerous cluster, and otherwise, the cluster is a safe cluster.

3. The distributed photovoltaic multi-cluster voltage control method of claim 1, wherein the locally regulating the voltage of the hazardous cluster comprises:

and dispatching an inverter with adjustable reactive power capacity in the danger cluster, and switching the inverter into an improved droop control mode to carry out on-site voltage regulation.

4. The distributed photovoltaic multi-cluster voltage control method of claim 1, wherein the determining of the cluster voltage deviation degree comprises:

obtaining each photovoltaic cluster microgrid based on a cluster division result;

for each node in the cluster, calculating the reactive voltage sensitivity of each node to the leading node;

and calculating to obtain the voltage deviation degree of each cluster according to the number of nodes in the cluster and the reactive voltage sensitivity.

5. The distributed photovoltaic multi-cluster voltage control method of claim 1, wherein the degree of voltage deviation is:

in the formula, M_θIs the cluster voltage deviation degree; n is the number of nodes in the cluster; u shape_iFor i-node real-time operation of voltage, S_iθReactive voltage sensitivity coefficient, U, for node i to dominant node θ_minFor minimum terminal voltage of each node in the cluster, U_maxAnd the maximum value of the terminal voltage of each node in the cluster.

6. The distributed photovoltaic multi-cluster voltage control method of claim 1, wherein the total amount of reactive power is:

in the formula,. DELTA.Q_jIncreasing the total reactive power of the photovoltaic inverter in the safety cluster; s_ijFor the reactive-voltage sensitivity factor, U, between the safety cluster leader node j and the hazard cluster leader node i_minFor minimum terminal voltage of each node in the cluster, U_maxFor maximum terminal voltage of each node in the cluster, U_iThe voltage is run in real time for the i-node.

7. The method of claim 1, wherein distributing reactive power to distributed photovoltaic power sources within a cluster based on the total amount of reactive power comprises:

establishing an active/reactive voltage sensitivity matrix between clusters and between nodes;

obtaining the relation between the node voltage amplitude variation and the power variation according to the node active/reactive voltage sensitivity matrix, and obtaining the difference value between the real-time voltage and the voltage rated value of the node;

and calculating to obtain the photovoltaic reactive variable quantity of each node according to the difference value between the real-time voltage of the node and the rated value, and obtaining the reactive power emitted by each distributed photovoltaic power supply in the cluster according to the photovoltaic reactive variable quantity K of each node and the reactive-voltage sensitivity factor, so that the reactive power is distributed to each distributed photovoltaic power supply in the cluster by the total reactive power quantity.

8. A distributed photovoltaic multi-cluster voltage control system, comprising:

the primary dividing module is used for preliminarily determining a safety cluster and a dangerous cluster by using a cluster dividing result and the cluster voltage deviation degree of each cluster, and carrying out local voltage regulation on the dangerous cluster;

the cluster determining module is used for calculating reactive-voltage sensitivity factors among the clusters if the local voltage regulation fails, and re-determining a safe cluster and a dangerous cluster according to the reactive-voltage sensitivity factors;

the power distribution module is used for selecting a safe cluster with the maximum sensitivity factor between the main guide node and the dangerous cluster main guide node in each cluster, enabling an inverter in the safe cluster to increase the total reactive power quantity delta Q, and distributing reactive power to each distributed photovoltaic power supply in the cluster based on the total reactive power quantity;

and the detection module is used for circularly detecting the voltage deviation degree of each cluster, re-determining the safe cluster if the cluster is still in a dangerous cluster, and otherwise, controlling the voltage stability of the power grid level when the voltage of each cluster is within the safety margin.

9. A computer readable storage medium storing one or more programs, the one or more programs comprising instructions, which when executed by a computing device, cause the computing device to perform any of the methods of claims 1-7.

10. A computing device, comprising: one or more processors, memory, and one or more programs stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions for performing any of the methods of claims 1-7.

Images