Reactive power voltage optimization method and system for distribution network

Abstract

The present invention belongs to the field of distribution network equipment management, and discloses a distribution network reactive voltage optimization method and system, the method includes S1, obtaining the operation data of the node, the operation data including the operation voltage and the operation current; S2, judging whether it is necessary to re-partition based on the operation data of the node, if so, entering S3, if not, taking the partition result of the previous reactive voltage optimization as the partition result of the reactive voltage optimization this time, entering S4; S3, partitioning the node based on the operation data to obtain the partition result; S4, performing reactive voltage optimization on the node based on the partition result to obtain the optimization result. The present invention can effectively reduce the probability of occurrence of events of partitions with low influence on the optimization result, thereby improving the efficiency of reactive voltage optimization of nodes in the distribution network.

Description

Technical Field

[0001] The present invention relates to the field of distribution network equipment management, and in particular to a distribution network reactive voltage optimization method and system. Background Art

[0002] Reactive power optimization refers to the optimization of certain performance indicators of the power system under the premise of meeting the corresponding constraints by optimizing the control variables under the given structural parameters and load conditions of the power system. This is an effective means to ensure the safe and economical operation of the power system, and it is also one of the important methods to improve the voltage quality of the power system. Therefore, the main significance of studying the reactive power optimization of the power system is to maintain a stable voltage level of the power system, improve the stability of the voltage, and reduce the active power loss by reasonably allocating the reactive power flow. In the prior art, when the reactive voltage optimization of the distribution network is performed, it is usually based on the operation data of the node, and the data of the node is obtained in a fixed period. When the number of nodes is large, it is necessary to partition the nodes to reduce the number of nodes in the objective function during a single reactive power optimization, thereby improving the efficiency of obtaining the optimization solution for the local area, and at the same time reducing the difficulty of reactive power optimization, because the number of nodes that need to be controlled in the local area is small. However, the prior art usually performs partitioning each time reactive power optimization is performed, without considering changes in the operating data of the node. If the operating data of the node remains basically unchanged, then the partitioning result obtained by partitioning again is very similar to the partitioning result obtained during the previous reactive power optimization, thereby affecting the efficiency of obtaining reactive voltage optimization results. Summary of the invention

[0003] The purpose of the present invention is to disclose a method and system for optimizing reactive power voltage in a distribution network, so as to solve the technical problems raised in the background technology.

[0004] In order to achieve the above object, the present invention adopts the following technical solution:

[0005] In a first aspect, the present invention provides a method for optimizing reactive power voltage in a distribution network, comprising:

[0006] S1, obtaining the operation data of the node, the operation data including the operation voltage and the operation current;

[0007] S2, based on the operation data of the node, determine whether re-partitioning is required. If so, enter S3. If not, use the partitioning result of the previous reactive power voltage optimization as the partitioning result of this reactive power voltage optimization, and enter S4.

[0008] S3, partition the nodes based on the running data and obtain the partition results;

[0009] S4, optimizing the reactive power and voltage of the nodes based on the partitioning results to obtain the optimization results;

[0010] The determination of whether repartitioning is required based on the running data of the node includes:

[0011] Calculate the coefficient of fluctuation in each region separately;

[0012] Calculate partition values ​​based on the volatility coefficient;

[0013] If the partition value is greater than the preset partition value threshold, it means that re-partitioning is required, otherwise, it means that re-partitioning is not required.

[0014] Preferably, obtaining the operation data of the node includes:

[0015] The operation data of the node is obtained using the preset acquisition cycle.

[0016] Preferably, the calculation formula of the fluctuation coefficient is:

[0017]

[0018] vola b,k represents the fluctuation coefficient corresponding to the reactive power voltage optimization of region b for the kth time; ub represents the set of nodes in region b, and nub represents the total number of nodes in region b;

[0019] siml k，j =η×Uc k,j +(1-η)×Ic k,j

[0020] η represents the weight, Uc k,j Represents the voltage monitoring value of node j, Ic k,j Represents the monitoring value of the current at node j.

[0021] Preferably, Uc k,j The calculation formula is:

[0022]

[0023] ns represents the set Uo k The number of operating voltages, Uo k To obtain the time in the time interval [t k -T,t k ] is a sequence of operating voltages of node j in FIG. 1 , where T represents a preset duration, and t k It indicates the time when the calculation of fluctuation coefficient starts when the reactive power voltage optimization is performed for the kth time, U s,k Indicates Uo k The sth operating voltage in ave,kIndicates Uo k The average value of the operating voltage, U s,k-1 Indicates Uo k-1 The sth operating voltage in k-1 Indicates that the acquisition time is in the time interval [t k-1 -T,t k-1 ] is a sequence of operating voltages of node j in t k-1 It indicates the time when the calculation of fluctuation coefficient starts when the reactive power voltage optimization is performed for the k-1th time, U ave,k-1 Indicates Uo k-1 The average value of the operating voltage in.

[0024] Preferably, Ic k,j The calculation formula is:

[0025]

[0026] I s,k Indicates that in Io k The sth operating current, Io k Indicates that the acquisition time is in the time interval [t k -T,t k ] is the sequence of the operating current of node j in ave,k Io k The average value of the running current, I s,k-1 Io k-1 The sth operating current in ave,k-1 Io k-1 The average value of the operating current, Io k-1 Indicates that the acquisition time is in the time interval [t k-1 -T,t k-1 ] is a sequence consisting of the operating current of node j in ].

[0027] Preferably, calculating the partition value based on the fluctuation coefficient includes:

[0028] Store all regions into the set areset;

[0029] Use the following formula to calculate the partition value:

[0030]

[0031] prtval represents the partition value, nare represents the total number of regions in areset, and vola i,k represents the volatility coefficient of region i in areset.

[0032] Preferably, the preset partition threshold is 0.05.

[0033] Preferably, partitioning the nodes based on the running data to obtain the partitioning results includes:

[0034] Calculate the partition characteristic value of the node based on the running data;

[0035] The nodes are partitioned based on the partition characteristic values ​​to obtain the partition results.

[0036] Preferably, the reactive power voltage optimization is performed on the node based on the partition result to obtain the optimization result, including:

[0037] Based on the zoning results, reactive power and voltage optimization is performed on each area to obtain the optimization results.

[0038] In a second aspect, the present invention provides a reactive voltage optimization system for a distribution network, comprising an acquisition module, a judgment module, a partitioning module and an optimization module;

[0039] The acquisition module is used to acquire the operation data of the node, and the operation data includes the operation voltage and the operation current;

[0040] The judgment module is used to judge whether repartitioning is required based on the operation data of the node;

[0041] The partitioning module is used to partition nodes based on running data and obtain partitioning results when re-partitioning is required;

[0042] The optimization module is used to optimize the reactive voltage of the node based on the partitioning result of the partitioning module when re-partitioning is required to obtain the optimization result, or,

[0043] When there is no need to re-partition, reactive voltage optimization is performed on the nodes based on the partition result of the previous reactive voltage optimization to obtain the optimization result.

[0044] Beneficial effects;

[0045] Compared with the prior art, the present invention does not partition each time when performing reactive voltage optimization, but first calculates the partition value, and then determines whether partitioning is required based on the partition value. This allows the present invention to effectively reduce the probability of occurrence of partition events with low impact on the optimization result during the reactive voltage optimization process, thereby improving the efficiency of reactive voltage optimization of nodes in the distribution network. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments are briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without creative work.

[0047] Figure 1 A schematic diagram of the reactive power voltage optimization method of the distribution network of the present invention.

[0048] Figure 2 A schematic diagram of the reactive power voltage optimization system for the distribution network of the present invention. DETAILED DESCRIPTION

[0049] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. The components of the embodiments of the present invention generally described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the claimed invention, but merely represents the selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without making creative work belong to the scope of protection of the present invention.

[0050] like Figure 1 In one embodiment shown, the present invention provides a method for optimizing reactive power voltage in a distribution network, comprising:

[0051] S1, obtaining the operation data of the node, the operation data including the operation voltage and the operation current;

[0052] S2, based on the operation data of the node, determine whether re-partitioning is required. If so, enter S3. If not, use the partitioning result of the previous reactive power voltage optimization as the partitioning result of this reactive power voltage optimization, and enter S4.

[0053] S3, partition the nodes based on the running data and obtain the partition results;

[0054] S4, optimizing the reactive power and voltage of the nodes based on the partitioning results to obtain the optimization results;

[0055] The determination of whether repartitioning is required based on the running data of the node includes:

[0056] Calculate the coefficient of fluctuation in each region separately;

[0057] Calculate partition values ​​based on the volatility coefficient;

[0058] If the partition value is greater than the preset partition value threshold, it means that re-partitioning is required, otherwise, it means that re-partitioning is not required.

[0059] In the above embodiment, when reactive voltage optimization is performed each time, partitioning is not performed each time, but the partition value is calculated first, and then whether partitioning is required is determined based on the partition value. This allows the present invention to effectively reduce the probability of occurrence of partitioning events with low impact on the optimization result during reactive voltage optimization, thereby improving the efficiency of reactive voltage optimization for nodes in the distribution network. This allows more efficient reactive voltage optimization to be performed on nodes in the distribution network.

[0060] Since the process of reactive voltage optimization is ongoing, when the average time required to obtain a reactive voltage optimization result once is reduced, the overall efficiency of reactive voltage optimization is effectively improved.

[0061] Specifically, if the amount of operating data is insufficient to support the calculation of partition values, partitioning is performed again each time reactive voltage optimization is performed. At the beginning of optimization, since the amount of operating data obtained is insufficient, it may be impossible to calculate the partition value. At this time, the present invention performs partitioning each time reactive voltage optimization is performed to reduce the complexity of the objective function.

[0062] Preferably, obtaining the operation data of the node includes:

[0063] The operation data of the node is obtained using the preset acquisition cycle.

[0064] Specifically, the preset acquisition period may be 5 seconds, that is, the operation data is acquired every 5 seconds.

[0065] In the process of obtaining the operating voltage and the operating current, both are obtained at the same time.

[0066] Preferably, the calculation formula of the fluctuation coefficient is:

[0067]

[0068] vola b,k represents the fluctuation coefficient corresponding to the reactive power voltage optimization of region b for the kth time; ub represents the set of nodes in region b, and nub represents the total number of nodes in region b;

[0069] siml k，j =η×Uc k,j +(1-η)×Ic k,j

[0070] η represents the weight, Uc k,j Represents the voltage monitoring value of node j, Ic k,j Represents the monitoring value of the current at node j.

[0071] The fluctuation coefficient is calculated based on the operating voltage and operating current of all nodes in the region. For region b, if there are more nodes with large voltage monitoring values ​​and more nodes with large current monitoring values ​​in region b, the corresponding fluctuation coefficient will be larger. The fluctuation coefficient is calculated from two different types of parameters, so that the calculated fluctuation coefficient can more accurately and timely represent the fluctuation of the overall operating voltage and operating current of the nodes in the region.

[0072] Specifically, the weight can be

[0073] Preferably, Uc k,j The calculation formula is:

[0074]

[0075] ns represents the set Uo k The number of operating voltages, Uo k To obtain the time in the time interval [t k -T,t k ] is a sequence of operating voltages of node j in FIG. 1 , where T represents a preset duration, and t k It indicates the time when the calculation of fluctuation coefficient starts when the reactive power voltage optimization is performed for the kth time, U s,k Indicates Uo k The sth operating voltage in ave,k Indicates Uo k The average value of the operating voltage, U s,k-1 Indicates Uo k-1 The sth operating voltage in k-1 Indicates that the acquisition time is in the time interval [t k-1 -T,t k-1 ] is a sequence of operating voltages of node j in t k-1 It indicates the time when the calculation of fluctuation coefficient starts when the reactive power voltage optimization is performed for the k-1th time, U ave,k-1 Indicates Uo k-1 The average value of the operating voltage in.

[0076] The present invention adopts the above calculation formula to calculate Uo k and Uo k-1 The similarity of the operating voltage in is calculated. The higher the similarity, the smaller the fluctuation of the operating voltage. k and Uo k-1 are all obtained based on T, so Uo k and Uo k-1 The present invention is not based solely on Uo kTo calculate the voltage monitoring value, the calculation result can include the change trend information of the operating voltage. The smaller the cosine similarity, the greater the trend change of the operating voltage. This calculation method is conducive to improving the accuracy of the calculated fluctuation coefficient, thereby improving the accuracy of the calculated partition value, and can more effectively reduce the probability of re-partitioning when the operating data changes little.

[0077] Specifically, the preset duration may be 5 minutes.

[0078] Preferably, Ic k,j The calculation formula is:

[0079]

[0080] I s,k Indicates that in Io k The sth operating current in k Indicates that the acquisition time is in the time interval [t k -T,t k ] is the sequence of the operating current of node j in ave,k Io k The average value of the running current, I s,k-1 Io k-1 The sth operating current in ave,k-1 Io k-1 The average value of the operating current, Io k-1 Indicates that the acquisition time is in the time interval [t k-1 -T,t k-1 ] is a sequence consisting of the operating current of node j in ].

[0081] The present invention adopts the above calculation formula to calculate Io k and Io k-1 The similarity of the running current in is calculated. The higher the similarity, the smaller the fluctuation of the running current. k and Io k-1 are all obtained based on T, so Io k and Io k-1 The same amount of running current is present in the

[0082] Preferably, calculating the partition value based on the fluctuation coefficient includes:

[0083] Store all regions into the set areset;

[0084] Use the following formula to calculate the partition value:

[0085]

[0086] prtval represents the partition value, nare represents the total number of regions in areset, and vola i,k represents the volatility coefficient of region i in areset.

[0087] The partition value of the present invention is calculated based on the fluctuation coefficients of all regions. The greater the difference between the fluctuation coefficients of the regions, the greater the partition value, indicating that the probability of re-partitioning is greater; the smaller the difference between the fluctuation coefficients of the regions, the smaller the partition value, indicating that the probability of re-partitioning is smaller. Therefore, the partition value of the present invention can more accurately indicate the possibility of re-partitioning.

[0088] Preferably, the preset partition threshold is 0.05.

[0089] Preferably, partitioning the nodes based on the running data to obtain the partitioning results includes:

[0090] Calculate the partition characteristic value of the node based on the running data;

[0091] The nodes are partitioned based on the partition characteristic values ​​to obtain the partition results.

[0092] Specifically, different from the existing partitioning methods, the present invention partitions directly based on partition feature values ​​without using algorithms such as clustering, so the partitioning can be obtained faster.

[0093] Preferably, the operating data also includes operating power.

[0094] Preferably, the calculation formula of the partition characteristic value is:

[0095]

[0096] feadpt q represents the partition characteristic value of node q, nd represents the total number of loads in the sequence Loadq, and Loadq represents the acquisition time in the time interval [t k -T,t k The sequence of operating voltages of nodes q in ], load v represents the vth load in Loadq, load max represents the maximum value of the load in Loadq, N1 represents the total number of nodes that meet the judgment rule within the range of q as the center and radius D; N2 represents the total number of nodes within the range of q as the center and radius D, w 1 and w 2 Represent the calculation weights of load and quantity respectively.

[0097] The partition characteristic value of the present invention is obtained by comprehensive calculation from two aspects: the degree of fluctuation of the load of the node within the specified time interval and the total number of nodes that meet the judgment rule within the specified range. Therefore, the greater the degree of fluctuation that meets the load judgment rule, the greater the total number of nodes, the greater the partition characteristic value. The partition characteristic value calculated in this way is conducive to dividing nodes with similar load fluctuations and similar load fluctuations of surrounding nodes into the same area, thereby improving the accuracy of the results of reactive voltage optimization for the area.

[0098] Specifically, the value of D is 1 kilometer.

[0099] Specifically, w 1 and w 2 The values ​​of can be and

[0100] Specifically, for a node r within a range of a circle with q as the center and a radius of D, the following method is used to determine whether r meets the determination rule:

[0101] like If it is less than the preset load threshold, it means that r meets the judgment rule, otherwise, r does not meet the judgment rule. ns represents the total number of loads in the sequence Loads, and Loads represents the acquisition time in the time interval [t k -T,t k ] is a sequence of operating voltages of nodes r in load u Indicates the uth load in Loads, load max,r Indicates the maximum value of the load in Loads.

[0102] Specifically, the load threshold is

[0103] Preferably, partitioning the nodes based on the partition feature values ​​to obtain partition results includes:

[0104] The first step is to save all nodes to the set Knd;

[0105] The second step is to randomly select a node from Knd as the partition target;

[0106] The third step is to store the partition target into a temporary set, delete the partition target from Knd, obtain the set Ncp of nodes adjacent to the partition target in Knd, and calculate the partition judgment value of each node in Ncp respectively;

[0107] Step 4: determine whether the maximum partition judgment value among all the partition judgment values ​​is greater than the set partition judgment value threshold. If so, proceed to step 5; if not, proceed to step 7;

[0108] Step 5: Determine whether there are still nodes in Knd. If so, proceed to step 6. If not, terminate the calculation and treat the nodes in each node set as nodes of the same partition.

[0109] Step 6: Use the maximum partition judgment value as the new partition target and proceed to step 3.

[0110] The seventh step is to determine whether there are still nodes in Knd. If so, create a new node set, store the nodes in the temporary set into the newly created node set, clear the elements in the temporary set, and go to the second step; if not, end the calculation and treat the nodes in each node set as nodes of the same partition.

[0111] The present invention does not use clustering to perform partitioning like the prior art, because the time complexity required for clustering is high, and the number of specified clusters must be achieved, which is obviously not suitable for distribution networks where the load is constantly changing. Therefore, the present invention takes each node as a partition target in turn, and obtains the partition judgment value between the nodes near the partition target and the adjacent nodes, so that the area can be extended along the direction where the partition characteristic value is most similar, which can improve the similarity of the nodes in the obtained area in load fluctuations and achieve more effective reactive voltage optimization. In addition, the present invention does not need to specify the number of areas in advance, and has a higher degree of adaptability.

[0112] Specifically, the newly created temporary set is an empty set.

[0113] Specifically, the calculation formula for the partition judgment value is:

[0114] dptjud z1,z2 =|feadpt z1 -feadpt z2 |

[0115] dptjud z1,z2 Indicates the partition judgment value between nodes z1 and z2, feadpt z1 and feadpt z2 Represent the partition feature values ​​of nodes z1 and z2 respectively.

[0116] Specifically, the partition judgment value threshold is 0.2.

[0117] Preferably, the reactive power voltage optimization is performed on the node based on the partition result to obtain the optimization result, including:

[0118] Based on the partition results, reactive power and voltage optimization is performed on the nodes in each area to obtain the optimization results.

[0119] Specifically, when optimizing reactive voltage, it is necessary to obtain operating data such as node load, voltage amplitude, branch conductance between nodes, and voltage difference between nodes.

[0120] The present invention focuses on whether to partition and the partitioning method in the optimization process, while the detailed process of optimizing the nodes by establishing the objective function based on the operation data belongs to the prior art and will not be described in detail in the present invention. For example, patents such as CN104319780A and CN118523339A have disclosed detailed reactive voltage optimization processes.

[0121] The optimization results include reactive voltage and active network loss at each node.

[0122] like Figure 2 In one embodiment shown, the present invention provides a reactive voltage optimization system for a distribution network, including an acquisition module, a judgment module, a partitioning module and an optimization module;

[0123] The acquisition module is used to acquire the operation data of the node, and the operation data includes the operation voltage and the operation current;

[0124] The judgment module is used to judge whether repartitioning is required based on the operation data of the node;

[0125] The partitioning module is used to partition nodes based on running data and obtain partitioning results when re-partitioning is required;

[0126] The optimization module is used to optimize the reactive voltage of the node based on the partitioning result of the partitioning module when re-partitioning is required to obtain the optimization result, or,

[0127] When there is no need to re-partition, reactive voltage optimization is performed on the nodes based on the partition result of the previous reactive voltage optimization to obtain the optimization result.

[0128] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A method for optimizing reactive power voltage in a distribution network, characterized in that: include: S1, obtaining the operation data of the node, the operation data including the operation voltage and the operation current; S2, judging whether re-partitioning is required based on the operation data of the node, if so, entering S3, if not, taking the partitioning result of the previous reactive power voltage optimization as the partitioning result of this reactive power voltage optimization, entering S4; S3, partition the nodes based on the running data and obtain the partition results; S4, optimizing the reactive power and voltage of the nodes based on the partitioning results to obtain the optimization results; The determination of whether repartitioning is required based on the running data of the node includes: Calculate the coefficient of fluctuation in each region separately; Calculate partition values ​​based on the volatility coefficient; If the partition value is greater than the preset partition value threshold, it means that re-partitioning is required, otherwise, it means that re-partitioning is not required; The calculation formula for the coefficient of volatility is: represents the fluctuation coefficient corresponding to the reactive power voltage optimization of region b for the kth time; ub represents the set of nodes in region b, and nub represents the total number of nodes in region b; represents the weight, represents the voltage monitoring value of node j, represents the monitoring value of node j in terms of current; Calculates partition values ​​based on volatility, including: Save all regions into a collection ; Use the following formula to calculate the partition value: Represents the partition value, express The total number of regions in express The coefficient of fluctuation of region i in .

2. The method for optimizing reactive power voltage in a distribution network according to claim 1, characterized in that: Get the running data of the node, including: The operation data of the node is obtained using the preset acquisition cycle.

3. The method for optimizing reactive power voltage in a distribution network according to claim 1, characterized in that: The calculation formula is: ns represents a set The number of operating voltages, To get the time in the time interval The sequence of the operating voltage of node j in , T represents the preset time length, It indicates the time when the calculation of fluctuation coefficient starts when the reactive power voltage optimization is performed for the kth time. express The sth operating voltage in express The average value of the operating voltage in express The sth operating voltage in Indicates that the acquisition time is in the time interval The sequence of operating voltages of node j in It indicates the time when the calculation of fluctuation coefficient starts when the reactive power voltage optimization is performed for the k-1th time. express The average value of the operating voltage in.

4. The method for optimizing reactive power voltage in a distribution network according to claim 3, characterized in that: The calculation formula is: Indicated in The sth operating current in Indicates that the acquisition time is in the time interval The sequence of operating currents of node j in express The average value of the running current in express The sth operating current in express The average value of the running current in Indicates that the acquisition time is in the time interval The sequence composed of the operating current of node j in .

5. The method for optimizing reactive power voltage in a distribution network according to claim 1, characterized in that: The default partition threshold is 0.

05.

6. The method for optimizing reactive power voltage in a distribution network according to claim 1, characterized in that: Partition the nodes based on the running data and obtain the partition results, including: Calculate the partition characteristic value of the node based on the running data; The nodes are partitioned based on the partition characteristic values ​​to obtain the partition results.

7. The method for optimizing reactive power voltage in a distribution network according to claim 1, characterized in that: Based on the partition results, the reactive power and voltage of the nodes are optimized to obtain the optimization results, including: Based on the zoning results, reactive power and voltage optimization is performed on each area to obtain the optimization results.

8. The reactive power voltage optimization system of the distribution network is characterized by: It includes acquisition module, judgment module, partition module and optimization module; The acquisition module is used to acquire the operation data of the node, and the operation data includes the operation voltage and the operation current; The judgment module is used to judge whether repartitioning is required based on the operation data of the node; The partitioning module is used to partition nodes based on running data and obtain partitioning results when re-partitioning is required; The optimization module is used to optimize the reactive voltage of the node based on the partitioning result of the partitioning module when re-partitioning is required to obtain the optimization result, or, When there is no need to re-partition, the reactive voltage optimization is performed on the node based on the partition result of the previous reactive voltage optimization to obtain the optimization result; The determination of whether repartitioning is required based on the running data of the node includes: Calculate the coefficient of fluctuation in each region separately; Calculate partition values ​​based on the volatility coefficient; If the partition value is greater than the preset partition value threshold, it means that re-partitioning is required, otherwise, it means that re-partitioning is not required; The calculation formula for the coefficient of volatility is: represents the fluctuation coefficient corresponding to the reactive power voltage optimization of region b for the kth time; ub represents the set of nodes in region b, and nub represents the total number of nodes in region b; represents the weight, represents the voltage monitoring value of node j, represents the monitoring value of node j in terms of current; Calculates partition values ​​based on volatility, including: Save all regions into a collection ; Use the following formula to calculate the partition value: Represents the partition value, express The total number of regions in express The coefficient of fluctuation of region i in .

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