A method and device for optimizing reactive power compensation in power system

Abstract

The present invention discloses a reactive power compensation optimization method and device for a power system. The present invention determines the relationship between all frequency modulation node frequencies and the reactive power of the whole network nodes according to the relationship between all frequency modulation node frequencies and the whole network node voltage, and the relationship between the reactive power of the whole network node and the whole network node voltage, and determines the relationship between the system inertia center frequency and the whole network node reactive power according to the relationship between the system inertia center frequency and all frequency modulation node frequencies, and obtains a target index characterizing the relationship between the reactive power of the whole network node and the system inertia center frequency and the whole network node voltage, and optimizes reactive power compensation by combining an objective function constructed with the minimum value of the target index as the optimization target and a reactive power compensation optimization model established according to the constraint conditions constructed based on the upper and lower limit constraints of the whole network node voltage and the upper and lower limit constraints of the reactive power of the whole network node, and can comprehensively consider the stability of the system inertia center frequency and the stability of the whole network node voltage to perform reactive power optimization compensation.

Description

Technical Field

[0001] The present invention relates to the technical field of power systems, and in particular to a method and device for optimizing reactive power compensation in a power system. Background Art

[0002] The stability of the power system is a highly concerned issue in the operation of the power system, which is mainly divided into frequency stability, voltage stability and synchronous stability. The instability of the power system is the result of the mutual coupling of multiple unstable phenomena. When the self-regulation ability is insufficient and it is not controlled by the outside world, some unstable phenomenon will eventually dominate and lead to the collapse of the power system.

[0003] At present, with the gradual increase in the penetration rate of new energy, the impact of frequency changes and voltage changes on the power system during operation is also gradually increasing. However, most of the existing power system reactive power compensation optimization methods only take voltage stability as the optimization target, which has limitations and cannot comprehensively consider frequency stability and voltage stability to optimize reactive power compensation of the power system. To a certain extent, it is difficult to effectively ensure the stable operation of the power system. Summary of the invention

[0004] In order to overcome the defects of the prior art, the present invention provides a method and device for optimizing reactive power compensation in an electric power system, which can comprehensively consider the stability of the system inertia center frequency and the stability of the node voltage of the entire network to perform reactive power optimization compensation, thereby effectively ensuring the stable operation of the power grid.

[0005] In order to solve the above technical problems, in a first aspect, an embodiment of the present invention provides a method for optimizing reactive power compensation in a power system, comprising:

[0006] Classify the synchronous machine nodes in the entire network into a number of first synchronous machine nodes, a number of second synchronous machine nodes and a number of third synchronous machine nodes; wherein the first synchronous machine nodes maintain the synchronous machine type and do not infiltrate, the second synchronous machine nodes infiltrate by incorporating the synchronous machine into the wind turbine, and the third synchronous machine nodes infiltrate by replacing the synchronous machine with the wind turbine;

[0007] Taking each first synchronous machine node and each second synchronous machine node as a frequency modulation node to obtain a plurality of frequency modulation nodes, and calculating the sensitivity matrix between the frequencies of all frequency modulation nodes and the node voltages of the entire network according to the relationship equation group between the frequencies of all frequency modulation nodes and the node voltages of the entire network to obtain a first sensitivity matrix;

[0008] Convert the PV nodes in the whole network nodes into PQ nodes, construct the sensitivity matrix between the reactive power of the whole network nodes and the voltage of the whole network nodes, and obtain the second sensitivity matrix;

[0009] Combining the first sensitivity matrix and the second sensitivity matrix, calculating the sensitivity matrix between the frequencies of all frequency modulation nodes and the reactive power of all network nodes, and obtaining a third sensitivity matrix;

[0010] According to the relationship equation between the system inertia center frequency and the frequencies of all frequency modulation nodes and the third sensitivity matrix, the relationship equation between the system inertia center frequency and the reactive power of all network nodes is calculated to obtain the target relationship equation;

[0011] According to the target relationship equation and the predefined grid node voltage stability index, the index representing the relationship between the grid node reactive power and the system inertia center frequency and the grid node voltage is calculated to obtain the target index;

[0012] The objective function is constructed with the minimum value of the target indicator as the optimization goal. Constraints are constructed according to the upper and lower limits of the voltage of the whole network nodes and the upper and lower limits of the reactive power of the whole network nodes. The reactive compensation optimization model is established by combining the objective function and the constraints to optimize the reactive compensation through the reactive compensation optimization model.

[0013] Furthermore, before calculating the sensitivity matrix between all frequency modulation node frequencies and the node voltages of the entire network according to the relationship equation group between all frequency modulation node frequencies and the node voltages of the entire network to obtain the first sensitivity matrix, the method further includes:

[0014] For each frequency modulation node, based on the synchronous machine primary frequency modulation formula, the relationship equation between the frequency modulation node frequency and the node voltage of the entire network is constructed;

[0015] According to the relationship equations between the frequencies of all frequency modulation nodes and the node voltages of the entire network, a group of relationship equations between the frequencies of all frequency modulation nodes and the node voltages of the entire network is obtained.

[0016] Furthermore, the primary frequency modulation formula of the synchronous machine is:

[0017]

[0018] Where ΔP i is the active power variation of frequency modulation node i; K Gi is the synchronous machine adjustment coefficient of frequency modulation node i; η i is the wind power penetration rate of frequency modulation node i. When frequency modulation node i is the first synchronous machine node, η i =0, when the frequency modulation node i is the second synchronous machine node, η i =η 1 , η 1 is the output ratio of the wind turbine to the synchronous machine at the frequency modulation node i; f i is the frequency of the frequency modulation node i after the disturbance; f N is the rated frequency of the system; is the active power of the frequency modulation node i represented by the voltage of the whole network after the disturbance, V i is the voltage of the frequency modulation node i, V j is the voltage of node j in the whole network, G ij and B ij are the mutual conductance and mutual susceptance between frequency modulation node i and network node j, θ ij is the voltage phase angle difference between frequency modulation node i and network node j; P i is the active power of frequency regulation node i under basic power flow.

[0019] Furthermore, according to the relationship equation group between the frequencies of all frequency modulation nodes and the node voltages of the entire network, the sensitivity matrix between the frequencies of all frequency modulation nodes and the node voltages of the entire network is calculated to obtain a first sensitivity matrix, which is specifically:

[0020] The partial derivatives of the relationship equations between the frequencies of all frequency modulation nodes and the voltages of all network nodes are obtained to obtain the first sensitivity matrix.

[0021] Furthermore, after converting the PV nodes in the whole network nodes into PQ nodes, constructing the sensitivity matrix between the reactive power of the whole network nodes and the voltage of the whole network nodes, and obtaining the second sensitivity matrix, the method further includes:

[0022] A new balancing node is selected from all the network nodes, the original balancing node is converted into a PQ node, the sensitivity matrix between the reactive power of all the network nodes and the voltage of all the network nodes is reconstructed, and the second sensitivity matrix is ​​updated.

[0023] Furthermore, the first sensitivity matrix and the second sensitivity matrix are combined to calculate the sensitivity matrix between the frequencies of all frequency modulation nodes and the reactive power of all network nodes to obtain a third sensitivity matrix, which is specifically:

[0024] The first sensitivity matrix is ​​multiplied by the second sensitivity matrix to obtain a third sensitivity matrix.

[0025] Furthermore, the relationship equation between the system inertia center frequency and all frequency modulation node frequencies is:

[0026]

[0027] Among them, f N is the rated frequency of the system; Δf COI is the change in the center frequency of the system’s inertia; m 1 is the total number of nodes of the first synchronization machine, m 2 is the total number of the second synchronization machine nodes; H i is the inertia of frequency modulation node i; Δf i is the voltage variation of frequency modulation node i; η 1 is the wind power penetration rate of the second synchronous machine node;

[0028] The target relationship equation is:

[0029]

[0030] Where n is the total number of nodes in the entire network; a ij is the element corresponding to the frequency change of frequency modulation node i and the reactive power change of node j in the whole network in the third sensitivity matrix, b j is the sensitivity coefficient between the change in the system inertia center frequency and the change in reactive power of node j in the whole network, ΔQ j is the reactive power change of node j in the whole network.

[0031] Furthermore, according to the target relationship equation and the predefined network node voltage stability index, the index characterizing the relationship between the network node reactive power and the system inertia center frequency and the network node voltage is calculated to obtain the target index, which is specifically:

[0032] The change in the inertia center frequency of the system obtained according to the target relationship equation is normalized, and the normalized change in the inertia center frequency of the system is added to the voltage stability index of the whole network node. The index representing the relationship between the reactive power of the whole network node and the system inertia center frequency and the voltage of the whole network node is calculated to obtain the target index.

[0033] Furthermore, the voltage stability index of the whole network node is:

[0034]

[0035] Where, ΔV sum is the voltage stability index of the whole network node; n is the total number of nodes in the whole network; ΔV j is the voltage change of node j in the whole network; V maxj is the maximum voltage of node j in the whole network; V j is the voltage of node j in the whole network under the reference power flow; c j is the reactive power change of node j in the whole network and the voltage stability index of the whole network node ΔV sum The sensitivity coefficient between j is the reactive power change of node j in the whole network;

[0036] The target indicators are:

[0037]

[0038] Among them, Z fV is the target indicator; Δf COI is the change in the center frequency of the inertia of the system; f N is the rated frequency of the system; d jis the reactive power change of node j in the whole network and the target index Z fV The sensitivity coefficient between .

[0039] In a second aspect, an embodiment of the present invention provides a reactive power compensation optimization device for a power system, comprising:

[0040] The whole network synchronous machine node classification module is used to classify the whole network synchronous machine nodes into a plurality of first synchronous machine nodes, a plurality of second synchronous machine nodes and a plurality of third synchronous machine nodes; wherein the first synchronous machine nodes maintain the synchronous machine type and do not infiltrate, the second synchronous machine nodes infiltrate by incorporating the synchronous machine into the wind turbine, and the third synchronous machine nodes infiltrate by replacing the synchronous machine with the wind turbine;

[0041] A first sensitivity matrix acquisition module is used to take each first synchronous machine node and each second synchronous machine node as a frequency modulation node to obtain a plurality of frequency modulation nodes, and calculate the sensitivity matrix between all frequency modulation node frequencies and the node voltage of the entire network according to the relationship equation group between the frequencies of all frequency modulation nodes and the node voltage of the entire network to obtain a first sensitivity matrix;

[0042] The second sensitivity matrix acquisition module is used to convert the PV nodes in the whole network nodes into PQ nodes, construct a sensitivity matrix between the reactive power of the whole network nodes and the voltage of the whole network nodes, and obtain a second sensitivity matrix;

[0043] A third sensitivity matrix acquisition module is used to combine the first sensitivity matrix and the second sensitivity matrix to calculate the sensitivity matrix between the frequency of all frequency modulation nodes and the reactive power of all network nodes to obtain a third sensitivity matrix;

[0044] A target relationship equation acquisition module is used to calculate the relationship equation between the system inertia center frequency and the reactive power of all network nodes according to the relationship equation between the system inertia center frequency and the frequencies of all frequency modulation nodes and the third sensitivity matrix to obtain the target relationship equation;

[0045] The target index acquisition module is used to calculate the index representing the relationship between the reactive power of the whole network node and the center frequency of the system inertia and the voltage of the whole network node according to the target relationship equation and the pre-defined whole network node voltage stability index to obtain the target index;

[0046] The power grid reactive power optimization compensation module is used to construct an objective function with the minimum value of the target indicator as the optimization target, construct constraint conditions according to the upper and lower limit constraints of the voltage of the whole network nodes and the upper and lower limit constraints of the reactive power of the whole network nodes, and establish a reactive power compensation optimization model in combination with the objective function and the constraint conditions, so as to optimize the reactive power compensation through the reactive power compensation optimization model.

[0047] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:

[0048] By determining the relationship between all frequency modulation node frequencies and the reactive power of all network nodes according to the relationship between the frequency of all frequency modulation nodes and the voltage of all network nodes, and the relationship between the reactive power of all network nodes and the voltage of all network nodes, and determining the relationship between the system inertia center frequency and the reactive power of all network nodes according to the relationship between the system inertia center frequency and the frequency of all frequency modulation nodes, the target index characterizing the relationship between the reactive power of all network nodes and the system inertia center frequency and the voltage of all network nodes is obtained. Reactive compensation optimization is performed by combining the objective function constructed with the minimum value of the target index as the optimization target and the reactive compensation optimization model established according to the constraints constructed based on the upper and lower limit constraints of the voltage of all network nodes and the upper and lower limit constraints of the reactive power of all network nodes. The reactive power optimization compensation can be performed by comprehensively considering the stability of the system inertia center frequency and the stability of the voltage of all network nodes, thereby effectively ensuring the stable operation of the power grid. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 A schematic flow chart of a method for optimizing reactive power compensation in a power system according to a first embodiment of the present invention;

[0050] Figure 2 It is a structural schematic diagram of a power system reactive power compensation optimization device in the second embodiment of the present invention. DETAILED DESCRIPTION

[0051] The technical solution of the present invention will be described clearly and completely below in conjunction with the accompanying drawings of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0052] It should be noted that the step numbers in the text are only for the convenience of explaining the specific embodiment and do not limit the order of execution of the steps. The method provided in this embodiment can be executed by a related terminal device, and the following description is taken as an example of a processor as the execution subject.

[0053] like Figure 1 As shown, the first embodiment provides a method for optimizing reactive power compensation in a power system, comprising steps S1 to S7:

[0054] S1. Classify the synchronous machine nodes in the whole network into a number of first synchronous machine nodes, a number of second synchronous machine nodes and a number of third synchronous machine nodes; wherein the first synchronous machine nodes maintain the synchronous machine type and do not infiltrate, the second synchronous machine nodes infiltrate by incorporating the synchronous machine into the wind turbine, and the third synchronous machine nodes infiltrate by replacing the synchronous machine with the wind turbine;

[0055] S2, taking each first synchronous machine node and each second synchronous machine node as a frequency modulation node to obtain a plurality of frequency modulation nodes, and calculating the sensitivity matrix between the frequencies of all frequency modulation nodes and the node voltages of the entire network according to the relationship equation group between the frequencies of all frequency modulation nodes and the node voltages of the entire network to obtain a first sensitivity matrix;

[0056] S3, converting the PV nodes in the whole network nodes into PQ nodes, constructing the sensitivity matrix between the reactive power of the whole network nodes and the voltage of the whole network nodes, and obtaining the second sensitivity matrix;

[0057] S4. Combining the first sensitivity matrix and the second sensitivity matrix, calculating the sensitivity matrix between the frequencies of all frequency modulation nodes and the reactive power of all network nodes, and obtaining a third sensitivity matrix;

[0058] S5. According to the relationship equation between the system inertia center frequency and the frequencies of all frequency modulation nodes and the third sensitivity matrix, the relationship equation between the system inertia center frequency and the reactive power of all network nodes is calculated to obtain the target relationship equation;

[0059] S6. According to the target relationship equation and the predefined network node voltage stability index, calculate the index representing the relationship between the network node reactive power and the system inertia center frequency and the network node voltage to obtain the target index;

[0060] S7. Construct an objective function with the minimum value of the target indicator as the optimization goal, construct constraint conditions according to the upper and lower limit constraints of the voltage of the whole network nodes and the upper and lower limit constraints of the reactive power of the whole network nodes, and establish a reactive compensation optimization model in combination with the objective function and the constraint conditions, so as to optimize the reactive compensation through the reactive compensation optimization model.

[0061] As an example, in step S1, m of the n nodes in the entire network are k The synchronizer nodes are classified into m k The synchronizer nodes are classified into m 1 The first synchronizer node that maintains the original synchronizer type and does not infiltrate, m 2 A second synchronous machine node and m 3 A third synchronous machine node is infiltrated by replacing the synchronous machine with a fan.

[0062] In step S2, when the selected wind turbine has inertia, the nodes that can participate in frequency modulation in the whole network include all first synchronous machine nodes and all second synchronous machine nodes. Each first synchronous machine node and each second synchronous machine node are used as frequency modulation nodes, and m is obtained. 1 +m 2Based on the disturbance of the active power of the system under the basic power flow, the relationship equation group between the frequency of all frequency modulation nodes and the node voltage of the whole network is constructed, and the sensitivity matrix between the frequency of all frequency modulation nodes and the node voltage of the whole network is calculated according to the relationship equation group between the frequency of all frequency modulation nodes and the node voltage of the whole network, and the first sensitivity matrix is ​​obtained.

[0063] In step S3, there are m PQ nodes and nm-1 PV nodes in the n nodes of the whole network, and the main frequency modulation node of the system is selected as the balancing node. In order to obtain the sensitivity matrix between the reactive power of the whole network node and the voltage of the whole network node by calculating the Jacobian matrix, the PV nodes in the whole network node are converted into PQ nodes, and the sensitivity matrix between the reactive power of the whole network node and the voltage of the whole network node is constructed to obtain the second sensitivity matrix.

[0064] In step S4, the first sensitivity matrix and the second sensitivity matrix are combined to calculate the sensitivity matrix between the frequencies of all frequency modulation nodes and the reactive power of all network nodes to obtain a third sensitivity matrix.

[0065] In step S5, according to the relationship equation between the system inertia center frequency and the frequencies of all frequency modulation nodes and the third sensitivity matrix, the relationship equation between the system inertia center frequency and the reactive power of all network nodes is calculated to obtain the target relationship equation.

[0066] In step S6, the grid node voltage stability index is predefined, and according to the target relationship equation and the predefined grid node voltage stability index, the index characterizing the relationship between the grid node reactive power and the system inertia center frequency and the grid node voltage is calculated to obtain the target index.

[0067] In step S7, an objective function is constructed with the minimum value of the target indicator as the optimization target, constraints are constructed according to the upper and lower limit constraints of the voltage of the nodes in the entire network and the upper and lower limit constraints of the reactive power of the nodes in the entire network, and a reactive compensation optimization model is established in combination with the objective function and the constraints to optimize reactive compensation through the reactive compensation optimization model.

[0068] This embodiment determines the relationship between all frequency modulation node frequencies and the reactive power of all network nodes according to the relationship between the frequencies of all frequency modulation nodes and the voltage of all network nodes, and the relationship between the reactive power of all network nodes and the voltage of all network nodes, and determines the relationship between the system inertia center frequency and the reactive power of all network nodes according to the relationship between the system inertia center frequency and the frequencies of all frequency modulation nodes, thereby obtaining a target index characterizing the relationship between the reactive power of all network nodes and the system inertia center frequency and the voltage of all network nodes. Reactive compensation optimization is performed by combining an objective function constructed with the minimum value of the target index as the optimization target and a reactive compensation optimization model established according to the constraints constructed with the upper and lower limits of the voltage of all network nodes and the upper and lower limits of the reactive power of all network nodes. This embodiment can comprehensively consider the stability of the system inertia center frequency and the stability of the voltage of all network nodes to perform reactive optimization compensation, thereby effectively ensuring the stable operation of the power grid.

[0069] In a preferred embodiment, before calculating the sensitivity matrix between all frequency modulation node frequencies and the node voltage of the whole network based on the relationship equation group between all frequency modulation node frequencies and the node voltage of the whole network to obtain the first sensitivity matrix, it also includes: for each frequency modulation node, constructing a relationship equation between the frequency modulation node frequency and the node voltage of the whole network based on the single frequency modulation formula of the synchronous machine; and obtaining the relationship equation group between all frequency modulation node frequencies and the node voltage of the whole network based on the relationship equation between all frequency modulation node frequencies and the node voltage of the whole network.

[0070] In a preferred embodiment, the synchronous machine primary frequency modulation formula is:

[0071]

[0072] Where ΔP i is the active power variation of frequency modulation node i; K Gi is the synchronous machine adjustment coefficient of frequency modulation node i; η i is the wind power penetration rate of frequency modulation node i. When frequency modulation node i is the first synchronous machine node, η i =0, when the frequency modulation node i is the second synchronous machine node, η i =η 1 , η 1 is the output ratio of the wind turbine to the synchronous machine at the frequency modulation node i; f i is the frequency of the frequency modulation node i after the disturbance; f N is the rated frequency of the system; is the active power of the frequency modulation node i represented by the voltage of the whole network after the disturbance, V i is the voltage of the frequency modulation node i, V j is the voltage of node j in the whole network, G ij and B ij are the mutual conductance and mutual susceptance between frequency modulation node i and network node j, θ ijis the voltage phase angle difference between frequency modulation node i and network node j; P i is the active power of frequency regulation node i under basic power flow.

[0073] As an example, for m 2 The second synchronous machine node is infiltrated by integrating the synchronous machine into the wind machine. The output ratio of the wind machine to the synchronous machine on each second synchronous machine node is η 1 .

[0074] In view of the disturbance of active power in the system under the basic flow, for each frequency regulation node, based on the synchronous machine primary frequency regulation formula, the relationship equation between the frequency of the frequency regulation node and the voltage of the whole network node can be constructed. The synchronous machine primary frequency regulation formula is as follows:

[0075]

[0076] In formula (1), ΔP i is the active power variation of frequency modulation node i; K Gi is the synchronous machine adjustment coefficient of frequency modulation node i; η i is the wind power penetration rate of frequency modulation node i. When frequency modulation node i is the first synchronous machine node, η i =0, when the frequency modulation node i is the second synchronous machine node, η i =η 1 , η 1 is the output ratio of the wind turbine to the synchronous machine at the frequency modulation node i; f i is the frequency of the frequency modulation node i after the disturbance; f N is the rated frequency of the system; is the active power of the frequency modulation node i represented by the voltage of the whole network after the disturbance, V i is the voltage of the frequency modulation node i, V j is the voltage of node j in the whole network, G ij and B ij are the mutual conductance and mutual susceptance between frequency modulation node i and network node j, θ ij is the voltage phase angle difference between frequency modulation node i and network node j; P i is the active power of frequency regulation node i under basic power flow.

[0077] According to the relationship equation between the frequency of all frequency modulation nodes and the voltage of the nodes in the whole network, the relationship equation group between the frequency of all frequency modulation nodes and the voltage of the nodes in the whole network is obtained. The relationship equation group between the frequency of all frequency modulation nodes and the voltage of the nodes in the whole network is as follows:

[0078]

[0079] In a preferred embodiment, the sensitivity matrix between all frequency modulation node frequencies and the node voltage of the entire network is calculated based on the relationship equation group between all frequency modulation node frequencies and the node voltage of the entire network to obtain a first sensitivity matrix. Specifically, the partial derivative of the relationship equation group between all frequency modulation node frequencies and the node voltage of the entire network is taken to obtain the first sensitivity matrix.

[0080] As an example, the relationship equation group between the frequency of all frequency modulation nodes and the voltage of the nodes in the whole network, that is, the partial derivative of both sides of equation (2) is obtained to obtain the sensitivity matrix between the frequency change of all frequency modulation nodes and the voltage change of the nodes in the whole network as the first sensitivity A 1 The first sensitivity matrix A 1 as follows:

[0081]

[0082] In a preferred embodiment, after converting the PV nodes in the entire network nodes into PQ nodes, constructing the sensitivity matrix between the reactive power of the entire network nodes and the voltage of the entire network nodes, and obtaining the second sensitivity matrix, it also includes: selecting a new balancing node from the entire network nodes, converting the original balancing node into a PQ node, reconstructing the sensitivity matrix between the reactive power of the entire network nodes and the voltage of the entire network nodes, and updating the second sensitivity matrix.

[0083] As an example, the power flow equation of the power system in polar coordinate form can be expressed as:

[0084] W = F(V,θ)(4);

[0085] In formula (4), W is the set of active power, reactive power of each PQ node and active power of PV node, V is the amplitude of the node voltage of the whole network, and θ is the phase angle of the node voltage of the whole network.

[0086] Assuming that there are m PQ nodes and nm-1 PV nodes among the n nodes in the whole network, the main frequency regulation node of the system is selected as the balancing node. In order to obtain the sensitivity matrix between the reactive power of the whole network node and the voltage of the whole network node through the calculation of the Jacobian matrix, the PV nodes in the whole network node are converted into PQ nodes. The specific expression is as follows:

[0087]

[0088] Construct the sensitivity matrix between the reactive power change of the whole network node and the voltage change of the whole network node as the second sensitivity matrix A 2 The second sensitivity matrix A 2 The matrix is ​​as follows:

[0089]

[0090] Since a balancing node must be selected to balance the power of the entire network during a power flow calculation, the main frequency modulation node of the system is generally selected as the balancing node, and the voltage of the balancing node is a known quantity and will not change during the calculation. Therefore, the second sensitivity matrix obtained based on the above method lacks the sensitivity relationship between the balancing node and other nodes and needs to be recalculated.

[0091] Reselect a new balancing node, convert the original balancing node into a PQ node, reconstruct the sensitivity matrix between the reactive power change of the whole network node and the voltage change of the whole network node and update it to the second sensitivity matrix A' 2 The second sensitivity matrix A' 2 as follows:

[0092]

[0093] In formula (7), is the influence vector of the reactive power of the original balancing node on the voltage of other nodes in the whole network except the new balancing node, is the influence vector of the original balancing node voltage on the reactive power of other nodes in the entire network except the new balancing node. The values ​​of the remaining elements in the matrix are similar to the results calculated previously and are not modified.

[0094] α 1 With α 2 Adding it to the second sensitivity matrix calculated previously, we can get an n×n sensitivity matrix A, which only lacks the relationship between reactive power and voltage between the new and old balancing nodes. We can select other nodes except these two points as new balancing nodes and repeat the above calculation to get a new second sensitivity matrix. However, due to the missing of the corresponding four elements, the impact on the Jacobian matrix with a huge number of elements is almost negligible, so no calculation is required. So far, we get the second sensitivity matrix A' 2 It reflects the relationship between the reactive power of the nodes in the whole network and the voltage of the nodes in the whole network.

[0095] In a preferred embodiment, the first sensitivity matrix and the second sensitivity matrix are combined to calculate the sensitivity matrix between the frequencies of all frequency modulation nodes and the reactive power of all network nodes to obtain a third sensitivity matrix, specifically: multiplying the first sensitivity matrix by the second sensitivity matrix to obtain the third sensitivity matrix.

[0096] As an example, by taking the first sensitivity matrix A 1 With the second sensitivity matrix A' 2 Multiply them together to obtain the sensitivity matrix between the frequency change of all frequency modulation nodes and the reactive power change of all network nodes as the third sensitivity matrix A 3 The third sensitivity matrix A 3 as follows:

[0097]

[0098] In a preferred embodiment, the relationship equation between the system inertia center frequency and all frequency modulation node frequencies is:

[0099]

[0100] Among them, f N is the rated frequency of the system; Δf COI is the change in the center frequency of the system’s inertia; m 1 is the total number of nodes of the first synchronization machine, m 2 is the total number of the second synchronization machine nodes; H i is the inertia of frequency modulation node i; Δf i is the voltage variation of frequency modulation node i; η 1 is the wind power penetration rate of the second synchronous machine node;

[0101] The target relationship equation is:

[0102]

[0103] Where n is the total number of nodes in the entire network; a ij is the element corresponding to the frequency change of frequency modulation node i and the reactive power change of node j in the whole network in the third sensitivity matrix, b j is the sensitivity coefficient between the change in the system inertia center frequency and the change in reactive power of node j in the whole network, ΔQ j is the reactive power change of node j in the whole network.

[0104] As an example, according to the relationship equation between the system inertia center frequency and all frequency modulation node frequencies, that is:

[0105]

[0106] In formula (9), f N is the rated frequency of the system; Δf COI is the change in the center frequency of the system’s inertia; m 1 is the total number of nodes of the first synchronization machine, m 2 is the total number of the second synchronization machine nodes; H i is the inertia of frequency modulation node i; Δf i is the voltage variation of frequency modulation node i; η 1 is the wind power penetration rate of the second synchronous machine node;

[0107] And the sensitivity matrix between the frequency change of all frequency modulation nodes and the reactive power change of all network nodes, that is, the third sensitivity matrix A 3, the relationship equation between the change in the system inertia center frequency and the change in reactive power of the whole network node can be obtained as the target relationship equation. The target relationship equation is:

[0108]

[0109] In formula (10), n is the total number of nodes in the whole network; a ij is the element corresponding to the frequency change of frequency modulation node i and the reactive power change of node j in the whole network in the third sensitivity matrix, b j is the sensitivity coefficient between the change in the system inertia center frequency and the change in reactive power of node j in the whole network, ΔQ j is the reactive power change of node j in the whole network.

[0110] In a preferred embodiment, the target relationship equation and the predefined network node voltage stability index are used to calculate the index characterizing the relationship between the network node reactive power and the system inertia center frequency and the network node voltage to obtain the target index. Specifically, the system inertia center frequency change obtained according to the target relationship equation is normalized, the normalized system inertia center frequency change and the network node voltage stability index are added, and the index characterizing the relationship between the network node reactive power and the system inertia center frequency and the network node voltage is calculated to obtain the target index.

[0111] In a preferred embodiment, the voltage stability index of the whole network node is:

[0112]

[0113] Where, ΔV sum is the voltage stability index of the whole network node; n is the total number of nodes in the whole network; ΔV j is the voltage change of node j in the whole network; V maxj is the maximum voltage of node j in the whole network; V j is the voltage of node j in the whole network under the reference power flow; c j is the reactive power change of node j in the whole network and the voltage stability index of the whole network node ΔV sum The sensitivity coefficient between j is the reactive power change of node j in the whole network;

[0114] The target indicators are:

[0115]

[0116] Among them, Z fV is the target indicator; Δf COI is the change in the center frequency of the inertia of the system; f N is the rated frequency of the system; d jis the reactive power change of node j in the whole network and the target index Z fV The sensitivity coefficient between .

[0117] As an example, by taking the inverse of the difference between the maximum voltage of the node and the voltage of the node under the reference flow as the weight, an index characterizing the stability of the node voltage of the whole network is constructed, that is, the node voltage stability index ΔV sum . Network node voltage stability index ΔV sum as follows:

[0118]

[0119] In formula (13), ΔV sum is the voltage stability index of the whole network node; n is the total number of nodes in the whole network; ΔV j is the voltage change of node j in the whole network; V maxj is the maximum voltage of node j in the whole network; V j is the voltage of node j in the whole network under the reference power flow.

[0120] The sensitivity matrix between the reactive power change of the whole network node and the voltage change of the whole network node is used, that is, the second sensitivity matrix A' 2 , we can get:

[0121]

[0122] In formula (11), ΔV sum is the voltage stability index of the whole network node; n is the total number of nodes in the whole network; ΔV j is the voltage change of node j in the whole network; V maxj is the maximum voltage of node j in the whole network; V j is the voltage of node j in the whole network under the reference power flow; c j is the reactive power change of node j in the whole network and the voltage stability index of the whole network node ΔV sum The sensitivity coefficient between j is the reactive power change of node j in the whole network.

[0123] The target relationship equation Δf COI After normalization, it is compared with the voltage stability index of the whole network node ΔV sum Adding, due to ΔV sum The calculation process has been normalized, so no further processing is required. The index that characterizes the relationship between the reactive power of the whole network node and the system inertia center frequency and the voltage of the whole network node is obtained as the target index Z fV .

[0124] Target indicator Z fV as follows:

[0125]

[0126] In formula (12), Z fV is the target indicator; Δf COI is the change in the center frequency of the inertia of the system; f N is the rated frequency of the system; d j is the reactive power change of node j in the whole network and the target index Z fV The sensitivity coefficient between .

[0127] When the target index is obtained, the objective function is constructed with the minimum value of the target index as the optimization goal, and the constraint conditions are constructed according to the upper and lower limit constraints of the voltage of the whole network nodes and the upper and lower limit constraints of the reactive power of the whole network nodes under the reference power flow. The constraint conditions are as follows:

[0128]

[0129] In formula (14), ΔU j is the voltage change of node j in the whole network; ΔU jmin , ΔU jmax are the minimum voltage change and the maximum voltage change of node j in the whole network respectively; ΔQ j is the reactive power change of node j in the whole network; ΔQ jmin , ΔQ jmax are the minimum reactive power change and the maximum reactive power change of node j in the whole network respectively.

[0130] A reactive compensation optimization model is established by combining the objective function and constraints. Reactive compensation is optimized through the reactive compensation optimization model to obtain a reactive compensation optimization scheme that takes into account the stability of the system inertia center frequency and the voltage stability of each node in the entire network.

[0131] Based on the same inventive concept as the first embodiment, the second embodiment provides Figure 2The reactive power compensation optimization device of the power system shown in the figure comprises: a whole-grid synchronous machine node classification module 21, which is used to classify the whole-grid synchronous machine nodes into a plurality of first synchronous machine nodes, a plurality of second synchronous machine nodes and a plurality of third synchronous machine nodes; wherein the first synchronous machine node maintains the synchronous machine type and does not infiltrate, the second synchronous machine node is infiltrated by incorporating the synchronous machine into the wind turbine, and the third synchronous machine node is infiltrated by replacing the synchronous machine with the wind turbine; a first sensitivity matrix acquisition module 22, which is used to take each first synchronous machine node and each second synchronous machine node as a frequency modulation node to obtain a plurality of frequency modulation nodes, and calculate the sensitivity matrix between the frequency of all frequency modulation nodes and the voltage of the whole-grid nodes according to the relationship equation group between the frequency of all frequency modulation nodes and the voltage of the whole-grid nodes, so as to obtain a first sensitivity matrix; a second sensitivity matrix acquisition module 23, which is used to convert the PV nodes in the whole-grid nodes into PQ nodes, construct a sensitivity matrix between the reactive power of the whole-grid nodes and the voltage of the whole-grid nodes, and obtain a second sensitivity matrix; The sensitivity matrix acquisition module 24 is used to calculate the sensitivity matrix between the frequency of all frequency modulation nodes and the reactive power of all network nodes in combination with the first sensitivity matrix and the second sensitivity matrix to obtain a third sensitivity matrix; the target relationship equation acquisition module 25 is used to calculate the relationship equation between the system inertia center frequency and the reactive power of all network nodes according to the relationship equation between the system inertia center frequency and the frequency of all frequency modulation nodes and the third sensitivity matrix to obtain the target relationship equation; the target indicator acquisition module 26 is used to calculate the indicator characterizing the relationship between the reactive power of all network nodes and the system inertia center frequency and the voltage of all network nodes according to the target relationship equation and the pre-defined network node voltage stability index to obtain the target indicator; the power grid reactive power optimization compensation module 27 is used to construct an objective function with the minimum value of the target indicator as the optimization target, construct constraint conditions according to the upper and lower limit constraints of the network node voltage and the upper and lower limit constraints of the network node reactive power, and establish a reactive compensation optimization model in combination with the objective function and the constraint conditions to optimize reactive compensation through the reactive compensation optimization model.

[0132] In a preferred embodiment, the first sensitivity matrix acquisition module 22 is also used to calculate the sensitivity matrix between all frequency modulation node frequencies and the node voltage of the whole network according to the relationship equation group between all frequency modulation node frequencies and the node voltage of the whole network, and before obtaining the first sensitivity matrix, for each frequency modulation node, based on the single frequency modulation formula of the synchronous machine, construct a relationship equation between the frequency of the frequency modulation node and the node voltage of the whole network, and according to the relationship equation between all frequency modulation node frequencies and the node voltage of the whole network, obtain the relationship equation group between all frequency modulation node frequencies and the node voltage of the whole network.

[0133] In a preferred embodiment, the synchronous machine primary frequency modulation formula is:

[0134]

[0135] Where ΔP i is the active power variation of frequency modulation node i; K Gi is the synchronous machine adjustment coefficient of frequency modulation node i; η i is the wind power penetration rate of frequency modulation node i. When frequency modulation node i is the first synchronous machine node, η i =0, when the frequency modulation node i is the second synchronous machine node, η i =η 1 , η 1 is the output ratio of the wind turbine to the synchronous machine at the frequency modulation node i; f i is the frequency of the frequency modulation node i after the disturbance; f N is the rated frequency of the system; is the active power of the frequency modulation node i represented by the voltage of the whole network after the disturbance, V i is the voltage of the frequency modulation node i, V j is the voltage of node j in the whole network, G ij and B ij are the mutual conductance and mutual susceptance between frequency modulation node i and network node j, θ ij is the voltage phase angle difference between frequency modulation node i and network node j; P i is the active power of frequency regulation node i under basic power flow.

[0136] In a preferred embodiment, the first sensitivity matrix acquisition module 22 is specifically used to obtain the first sensitivity matrix by taking partial derivatives of the relationship equation group between the frequencies of all frequency modulation nodes and the voltages of all network nodes.

[0137] In a preferred embodiment, the second sensitivity matrix acquisition module 23 is also used to convert the PV nodes in the whole network nodes into PQ nodes, construct the sensitivity matrix between the reactive power of the whole network nodes and the voltage of the whole network nodes, and after obtaining the second sensitivity matrix, select a new balancing node from the whole network nodes, convert the original balancing node into a PQ node, reconstruct the sensitivity matrix between the reactive power of the whole network nodes and the voltage of the whole network nodes, and update the second sensitivity matrix.

[0138] In a preferred embodiment, the third sensitivity matrix acquisition module 24 is specifically configured to multiply the first sensitivity matrix by the second sensitivity matrix to obtain a third sensitivity matrix.

[0139] In a preferred embodiment, the relationship equation between the system inertia center frequency and all frequency modulation node frequencies is:

[0140]

[0141] Among them, f N is the rated frequency of the system; Δf COIis the change in the center frequency of the system’s inertia; m 1 is the total number of nodes of the first synchronization machine, m 2 is the total number of the second synchronization machine nodes; H i is the inertia of frequency modulation node i; Δf i is the voltage variation of frequency modulation node i; η 1 is the wind power penetration rate of the second synchronous machine node;

[0142] The target relationship equation is:

[0143]

[0144] Where n is the total number of nodes in the entire network; a ij is the element corresponding to the frequency change of frequency modulation node i and the reactive power change of node j in the whole network in the third sensitivity matrix, b j is the sensitivity coefficient between the change in the system inertia center frequency and the change in reactive power of node j in the whole network, ΔQ j is the reactive power change of node j in the whole network.

[0145] In a preferred embodiment, the target indicator acquisition module 26 is specifically used to normalize the change in the inertia center frequency of the system obtained according to the target relationship equation, add the normalized change in the inertia center frequency of the system and the voltage stability index of the whole network node, calculate the index characterizing the relationship between the reactive power of the whole network node and the system inertia center frequency and the node voltage of the whole network, and obtain the target indicator.

[0146] In a preferred embodiment, the voltage stability index of the whole network node is:

[0147]

[0148] Where, ΔV sum is the voltage stability index of the whole network node; n is the total number of nodes in the whole network; ΔV j is the voltage change of node j in the whole network; V maxj is the maximum voltage of node j in the whole network; V j is the voltage of node j in the whole network under the reference power flow; c j is the reactive power change of node j in the whole network and the voltage stability index of the whole network node ΔV sum The sensitivity coefficient between j is the reactive power change of node j in the whole network;

[0149] The target indicators are:

[0150]

[0151] Among them, Z fVis the target indicator; Δf COI is the change in the center frequency of the inertia of the system; f N is the rated frequency of the system; d j is the reactive power change of node j in the whole network and the target index Z fV The sensitivity coefficient between .

[0152] In summary, the implementation of the embodiments of the present invention has the following beneficial effects:

[0153] By determining the relationship between all frequency modulation node frequencies and the reactive power of all network nodes according to the relationship between the frequency of all frequency modulation nodes and the voltage of all network nodes, and the relationship between the reactive power of all network nodes and the voltage of all network nodes, and determining the relationship between the system inertia center frequency and the reactive power of all network nodes according to the relationship between the system inertia center frequency and the frequency of all frequency modulation nodes, the target index characterizing the relationship between the reactive power of all network nodes and the system inertia center frequency and the voltage of all network nodes is obtained. Reactive compensation optimization is performed by combining the objective function constructed with the minimum value of the target index as the optimization target and the reactive compensation optimization model established according to the constraints constructed based on the upper and lower limit constraints of the voltage of all network nodes and the upper and lower limit constraints of the reactive power of all network nodes. The reactive power optimization compensation can be performed by comprehensively considering the stability of the system inertia center frequency and the stability of the voltage of all network nodes, thereby effectively ensuring the stable operation of the power grid.

[0154] The above is a preferred embodiment of the present invention. It should be pointed out that a person skilled in the art can make several improvements and modifications without departing from the principle of the present invention. These improvements and modifications are also considered to be within the scope of protection of the present invention.

[0155] Those skilled in the art can understand that all or part of the processes in the above embodiments can be implemented by instructing related hardware through a computer program, and the program can be stored in a computer-readable storage medium, and when the program is executed, it can include the processes in the above embodiments. The storage medium can be a disk, an optical disk, a read-only memory (ROM) or a random access memory (RAM), etc.

Claims

1. A method for optimizing reactive power compensation in a power system. It is characterized in that include: Classify the synchronous machine nodes in the entire network into a number of first synchronous machine nodes, a number of second synchronous machine nodes and a number of third synchronous machine nodes; wherein the first synchronous machine nodes maintain the synchronous machine type and do not infiltrate, the second synchronous machine nodes infiltrate by incorporating the synchronous machine into the wind turbine, and the third synchronous machine nodes infiltrate by replacing the synchronous machine with the wind turbine; Taking each first synchronous machine node and each second synchronous machine node as a frequency modulation node to obtain a plurality of frequency modulation nodes, and calculating the sensitivity matrix between the frequencies of all frequency modulation nodes and the node voltages of the entire network according to the relationship equation group between the frequencies of all frequency modulation nodes and the node voltages of the entire network to obtain a first sensitivity matrix; Convert the PV nodes in the whole network nodes into PQ nodes, construct the sensitivity matrix between the reactive power of the whole network nodes and the voltage of the whole network nodes, and obtain the second sensitivity matrix; Combining the first sensitivity matrix and the second sensitivity matrix, calculating the sensitivity matrix between the frequencies of all frequency modulation nodes and the reactive power of all network nodes, and obtaining a third sensitivity matrix; According to the relationship equation between the system inertia center frequency and the frequencies of all frequency modulation nodes and the third sensitivity matrix, the relationship equation between the system inertia center frequency and the reactive power of all network nodes is calculated to obtain the target relationship equation; According to the target relationship equation and the predefined grid node voltage stability index, the index representing the relationship between the grid node reactive power and the system inertia center frequency and the grid node voltage is calculated to obtain the target index; The objective function is constructed with the minimum value of the target indicator as the optimization goal. Constraints are constructed according to the upper and lower limits of the voltage of the whole network nodes and the upper and lower limits of the reactive power of the whole network nodes. The reactive compensation optimization model is established by combining the objective function and the constraints to optimize the reactive compensation through the reactive compensation optimization model.

2. The method for optimizing reactive power compensation in a power system according to claim 1, It is characterized in that Before calculating the sensitivity matrix between all frequency modulation node frequencies and the node voltages of the entire network according to the relationship equation group between all frequency modulation node frequencies and the node voltages of the entire network to obtain the first sensitivity matrix, the method further includes: For each frequency modulation node, based on the synchronous machine primary frequency modulation formula, the relationship equation between the frequency modulation node frequency and the node voltage of the entire network is constructed; According to the relationship equations between the frequencies of all frequency modulation nodes and the node voltages of the entire network, a group of relationship equations between the frequencies of all frequency modulation nodes and the node voltages of the entire network is obtained.

3. The method for optimizing reactive power compensation in a power system according to claim 2, It is characterized in that The primary frequency modulation formula of the synchronous machine is: Among them, ΔP i is the active power variation of frequency modulation node i; K Gi is the synchronous machine adjustment coefficient of frequency modulation node i; η i is the wind power penetration rate of frequency modulation node i. When frequency modulation node i is the first synchronous machine node, η i =0, when the frequency modulation node i is the second synchronous machine node, η i =η 1 , η 1 is the output ratio of the wind turbine to the synchronous machine at the frequency modulation node i; f i is the frequency of the frequency modulation node i after the disturbance; f N is the rated frequency of the system; is the active power of the frequency modulation node i represented by the voltage of the whole network after the disturbance, V i is the voltage of the frequency modulation node i, V j is the voltage of node j in the whole network, G ij and B ij are the mutual conductance and mutual susceptance between frequency modulation node i and network node j, θ ij is the voltage phase angle difference between frequency modulation node i and network node j; P i is the active power of frequency regulation node i under basic power flow.

4. The method for optimizing reactive power compensation in a power system according to claim 1, It is characterized in that According to the relationship equation group between all frequency modulation node frequencies and the node voltages of the entire network, the sensitivity matrix between all frequency modulation node frequencies and the node voltages of the entire network is calculated to obtain a first sensitivity matrix, which is specifically: The partial derivatives of the relationship equations between the frequencies of all frequency modulation nodes and the voltages of all network nodes are obtained to obtain the first sensitivity matrix.

5. The method for optimizing reactive power compensation in a power system according to claim 1, It is characterized in that After converting the PV nodes in the whole network nodes into PQ nodes, constructing the sensitivity matrix between the reactive power of the whole network nodes and the voltage of the whole network nodes, and obtaining the second sensitivity matrix, the method further includes: A new balancing node is selected from all the network nodes, the original balancing node is converted into a PQ node, the sensitivity matrix between the reactive power of all the network nodes and the voltage of all the network nodes is reconstructed, and the second sensitivity matrix is ​​updated.

6. The method for optimizing reactive power compensation in a power system according to claim 1, It is characterized in that The first sensitivity matrix and the second sensitivity matrix are combined to calculate the sensitivity matrix between the frequencies of all frequency modulation nodes and the reactive power of all network nodes to obtain a third sensitivity matrix, which is specifically: The first sensitivity matrix is ​​multiplied by the second sensitivity matrix to obtain a third sensitivity matrix.

7. The method for optimizing reactive power compensation in a power system according to claim 1, It is characterized in that The relationship equation between the system inertia center frequency and all frequency modulation node frequencies is: Among them, f N is the rated frequency of the system; Δf COI is the change in the center frequency of the system’s inertia; m 1 is the total number of nodes of the first synchronization machine, m 2 is the total number of the second synchronization machine nodes; H i is the inertia of frequency modulation node i; Δf i is the voltage variation of frequency modulation node i; η 1 is the wind power penetration rate of the second synchronous machine node; the target relationship equation is: Where n is the total number of nodes in the entire network; a ij is the element corresponding to the frequency change of frequency modulation node i and the reactive power change of node j in the whole network in the third sensitivity matrix, b j is the sensitivity coefficient between the change in the system inertia center frequency and the change in reactive power of node j in the whole network, ΔQ j is the reactive power change of node j in the whole network.

8. The method for optimizing reactive power compensation in a power system according to claim 1, It is characterized in that According to the target relationship equation and the predefined network node voltage stability index, the index characterizing the relationship between the network node reactive power and the system inertia center frequency and the network node voltage is calculated to obtain the target index, which is specifically: The change in the inertia center frequency of the system obtained according to the target relationship equation is normalized, and the normalized change in the inertia center frequency of the system is added to the voltage stability index of the whole network node. The index representing the relationship between the reactive power of the whole network node and the system inertia center frequency and the voltage of the whole network node is calculated to obtain the target index.

9. The method for optimizing reactive power compensation in a power system according to claim 8, It is characterized in that The voltage stability index of the whole network node is: Where, ΔV sum is the voltage stability index of the whole network node; n is the total number of nodes in the whole network; ΔV j is the voltage change of node j in the whole network; V maxj is the maximum voltage of node j in the whole network; V j is the voltage of node j in the whole network under the reference power flow; c j is the reactive power change of node j in the whole network and the voltage stability index of the whole network node ΔV sum The sensitivity coefficient between j is the reactive power change of node j in the whole network; The target indicators are: Among them, Z fV is the target indicator; Δf COI is the change in the center frequency of inertia of the system; f N is the rated frequency of the system; d j is the reactive power change of node j in the whole network and the target index Z fV The sensitivity coefficient between .

10. A reactive power compensation optimization device for a power system, It is characterized in that include: The whole network synchronous machine node classification module is used to classify the whole network synchronous machine nodes into a plurality of first synchronous machine nodes, a plurality of second synchronous machine nodes and a plurality of third synchronous machine nodes; wherein the first synchronous machine nodes maintain the synchronous machine type and do not infiltrate, the second synchronous machine nodes infiltrate by incorporating the synchronous machine into the wind turbine, and the third synchronous machine nodes infiltrate by replacing the synchronous machine with the wind turbine; A first sensitivity matrix acquisition module is used to take each first synchronous machine node and each second synchronous machine node as a frequency modulation node to obtain a plurality of frequency modulation nodes, and calculate the sensitivity matrix between all frequency modulation node frequencies and the node voltage of the entire network according to the relationship equation group between the frequencies of all frequency modulation nodes and the node voltage of the entire network to obtain a first sensitivity matrix; The second sensitivity matrix acquisition module is used to convert the PV nodes in the whole network nodes into PQ nodes, construct a sensitivity matrix between the reactive power of the whole network nodes and the voltage of the whole network nodes, and obtain a second sensitivity matrix; A third sensitivity matrix acquisition module is used to combine the first sensitivity matrix and the second sensitivity matrix to calculate the sensitivity matrix between the frequency of all frequency modulation nodes and the reactive power of all network nodes to obtain a third sensitivity matrix; A target relationship equation acquisition module is used to calculate the relationship equation between the system inertia center frequency and the reactive power of all network nodes according to the relationship equation between the system inertia center frequency and the frequencies of all frequency modulation nodes and the third sensitivity matrix to obtain the target relationship equation; The target index acquisition module is used to calculate the index representing the relationship between the reactive power of the whole network node and the center frequency of the system inertia and the voltage of the whole network node according to the target relationship equation and the pre-defined whole network node voltage stability index to obtain the target index; The power grid reactive power optimization compensation module is used to construct an objective function with the minimum value of the target indicator as the optimization target, construct constraint conditions according to the upper and lower limit constraints of the voltage of the whole network nodes and the upper and lower limit constraints of the reactive power of the whole network nodes, and establish a reactive power compensation optimization model in combination with the objective function and the constraint conditions, so as to optimize the reactive power compensation through the reactive power compensation optimization model.

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