A method and device for predicting three-phase imbalance of distribution network based on digital twin

Abstract

The present invention relates to the technical field of fault warning of distribution network, and specifically provides a method and device for predicting three-phase imbalance of distribution network based on digital twin, including: determining the state transfer probability distribution of three-phase load at the node of distribution network at the next moment based on the state transfer probability of three-phase load at the node of distribution network at the current moment and the three-phase load state transfer probability matrix; determining the active power and reactive power of the node of distribution network at the next moment based on the state transfer probability distribution of three-phase load at the node of distribution network at the next moment; iteratively solving the three-phase current injected into the node of distribution network at the next moment by using the active power and reactive power of the node of distribution network at the next moment; predicting the three-phase imbalance of the node of distribution network at the next moment based on the three-phase current injected into the node of distribution network at the next moment. The scheme can objectively and comprehensively predict the three-phase imbalance of distribution network, and provide a reference basis for the analysis and management of three-phase imbalance situation of distribution network.

Description

Technical Field

[0001] The present invention relates to the field of distribution network fault early warning, and in particular to a distribution network three-phase imbalance prediction method and device based on digital twin. Background Art

[0002] In the distribution network planning process, the single-phase load will be evenly allocated in the three-phase lines A, B, and C to ensure the symmetry of the three-phase load of the distribution network. However, due to the actual power consumption status of residential users, the single-phase load demand at the same time has certain differences and random fluctuations, which leads to unbalanced three-phase load, and to a certain extent affects the three-phase imbalance index of the distribution network. The unbalanced three-phase load of the distribution network will lead to a series of problems such as reduced voltage quality of the distribution network, increased line loss, and reduced available capacity of the distribution transformer.

[0003] At present, in most cases, the three-phase imbalance of the distribution network is obtained by direct measurement, without considering the impact of user behavior characteristics on the three-phase imbalance of the distribution network, and it is impossible to dynamically obtain the change trend of the three-phase imbalance of the distribution network. Therefore, a distribution network three-phase imbalance prediction method based on digital twins is urgently needed. Summary of the invention

[0004] In order to overcome the above-mentioned defects, the present invention proposes a method and device for predicting three-phase imbalance of distribution network based on digital twin.

[0005] In a first aspect, a method for predicting three-phase imbalance of a distribution network based on digital twin is provided, and the method for predicting three-phase imbalance of a distribution network based on digital twin comprises:

[0006] Obtain the node three-phase load state transfer probability and three-phase load state transfer probability matrix of the distribution network at the current moment;

[0007] Determine the state transition probability distribution of the three-phase load at the node of the distribution network at the next moment based on the state transition probability of the three-phase load at the node of the distribution network at the current moment and the three-phase load state transition probability matrix;

[0008] Determine the active power and reactive power of the nodes in the distribution network at the next moment based on the state transition probability distribution of the three-phase load of the nodes in the distribution network at the next moment;

[0009] The three-phase current injected into the node of the distribution network at the next moment is iteratively solved by using the active power and reactive power of the node of the distribution network at the next moment;

[0010] The three-phase imbalance degree of the nodes in the distribution network at the next moment is predicted based on the three-phase current injected into the nodes in the distribution network at the next moment.

[0011] Preferably, the current time is T r +Kt r , where Tr is the current sampling time of the system, K is the preset time interval between the current sampling time of the system and the current moment, t r is the preset time interval.

[0012] Furthermore, the calculation formula for the node three-phase load state transition probability of the distribution network at the current moment is as follows:

[0013]

[0014] The calculation formula of the node three-phase load state transfer probability matrix of the distribution network at the current moment is as follows:

[0015]

[0016] In the above formula, is the load state transition probability of phase φ at node i in the distribution network at the current moment, is the number of times that the number of devices turned on in phase φ of node i of the distribution network changes from x to y at the current moment. is the total number of changes in the number of devices turned on at the i-th node of the distribution network at the current moment, is the load state transfer probability matrix of the φ phase of the i-th node in the distribution network at the current moment, x, y∈[1,M], M is the total number of devices connected to the distribution network nodes, φ∈[a,b,c].

[0017] Furthermore, the calculation formula for the state transition probability distribution of the three-phase load of the node in the distribution network at the next moment is as follows:

[0018]

[0019] In the above formula, is the state transition probability distribution of the φ-phase load of node i in the distribution network at the next moment, is the distribution network T r When the state transition probability distribution of the load of node i is is the load state transfer probability matrix of the phase i of the distribution network at the last moment, is the load state transition probability matrix of the i-node φ phase in the distribution network at K moments;

[0020] Among them, the distribution network T r The calculation formula for the state transition probability distribution of the φ-phase load of node i is as follows:

[0021]

[0022] In the above formula, is the distribution network T r When the power of the Mth connected device of node i is T rThe probability of the power collected by the system when

[0023] Furthermore, the calculation formula of the active power of the node of the distribution network at the next moment is as follows:

[0024]

[0025] The calculation formula of the reactive power of the node of the distribution network at the next moment is as follows:

[0026]

[0027] In the above formula, is the active power of phase φ of node i in the distribution network at the next moment, is the state transition probability distribution of the three-phase load at the node of the distribution network at the next moment The mathematical expectation, P eφm is the rated power of the mth device connected to the node φ of the distribution network i, is the φ-phase reactive power of node i in the distribution network at the next moment, is the power factor angle of the mth device connected to the node φ of the distribution network i.

[0028] Furthermore, the method of iteratively solving the three-phase current injected into the node of the distribution network at the next moment by using the active power and reactive power of the node of the distribution network at the next moment includes:

[0029] Step 1: Initialize the three-phase voltage of node i of the 0th iteration distribution network to distribution network T r The three-phase voltage of node i collected by the system is initialized to k=0;

[0030] Step 2 determines the three-phase complex power of node i at the next moment of the distribution network based on the active power and reactive power of node i at the next moment of the distribution network;

[0031] Step 3 determines the three-phase current injected into the i node at the next moment of the k-th iteration distribution network based on the three-phase complex power of the i node at the next moment of the distribution network and the three-phase voltage of the i node at the k-th iteration distribution network;

[0032] Step 4: determine the branch current matrix of the k+1th iteration distribution network at the next moment by using the three-phase current injected by the i node at the next moment of the k-th iteration distribution network, and obtain the three-phase current injected by the i node at the next moment of the k+1th iteration distribution network from the branch current matrix of the k+1th iteration distribution network at the next moment;

[0033] Step 5: Determine the k+1th iteration distribution network node voltage matrix using the three-phase current injected into the i node of the k+1th iteration distribution network at the next moment, and obtain the three-phase voltage of the i node of the k+1th iteration distribution network from the k+1th iteration distribution network node voltage matrix;

[0034] Step 6 determines whether the absolute value of the difference between the three-phase voltage of the i node of the k+1th iteration distribution network and the three-phase voltage of the i node of the kth iteration distribution network is less than a preset value. If so, the three-phase current injected into the i node of the k+1th iteration distribution network at the next moment is used as the three-phase current injected into the node of the distribution network at the next moment, and the three-phase current injected into the node of the distribution network at the next moment is output. Otherwise, set k=k+1 and return to step 3.

[0035] Furthermore, the calculation formula of the three-phase complex power of the node i at the next moment of the distribution network is as follows:

[0036]

[0037] In the above formula, is the complex power of phase φ of node i in the distribution network at the next moment, and j is an imaginary unit.

[0038] Furthermore, the calculation formula of the three-phase current injected into the node i at the next moment of the k-th iteration of the distribution network is as follows:

[0039]

[0040] In the above formula, is the three-phase current injected into node i at the next moment of the k-th iteration distribution network, are the A, B, and C phase currents injected into node i at the next moment of the k-th iteration of the distribution network, are the complex power of phases A, B, and C of node i in the distribution network at the next moment, They are the phase voltages of node A, B, and C at the next moment of the k-th iteration of the distribution network.

[0041] Furthermore, the calculation formula of the branch current matrix of the distribution network at the next moment of the k+1th iteration is as follows:

[0042]

[0043] In the above formula, is the branch current matrix of the k+1th iteration distribution network at the next moment, A is the distribution network node branch association matrix, E A is the identity matrix, is the branch current matrix of the k-th iteration distribution network at the next moment, I (k) is the three-phase current vector injected into each node of the k-th iteration distribution network at the next moment, N is the total number of distribution network nodes;

[0044] Among them, the distribution network node branch association matrix A is a 3N×3N order square matrix, and its calculation formula is as follows:

[0045] A=[A ij ]

[0046] In the above formula, i,j∈[1,N], if the i node is related to the j node in the distribution network, and the direction of the i node is away from the j node, then A ij is a 3×3 unit matrix. If node i is related to node j in the distribution network and the direction of node i is toward node j, then A ij is a negative 3×3 unit matrix. If the i node and the j node in the distribution network are unrelated, then A ij is a 3×3 zero matrix.

[0047] Furthermore, the calculation formula of the k+1th iteration distribution network node voltage matrix is ​​as follows:

[0048]

[0049] In the above formula, U (k+1) is the k+1th iteration distribution network node voltage matrix, U s is the three-phase voltage of the bus node at the grid connection point, U (k) is the kth iteration distribution network node voltage matrix, Z L is the distribution network impedance matrix;

[0050] The calculation formula of the distribution network impedance matrix is ​​as follows:

[0051]

[0052] In the above formula, Z iAA , Z iBB , Z iCC are the self-impedances of phases A, B, and C at node i in the distribution network, and Z iAB , Z iBC , Z iCA are the mutual impedances of nodes AB, BC, and CA in the distribution network, respectively, and Z iAB =Z iBA , Z iBC =Z iCB , Z iCA =Z iAC .

[0053] Preferably, the calculation formula of the three-phase unbalance degree of the node of the distribution network at the next moment is as follows:

[0054]

[0055] In the above formula, is the three-phase unbalance degree of node i in the distribution network at the next moment, They are respectively the A, B, and C phase currents injected into node i of the distribution network at the next moment.

[0056] In a second aspect, a three-phase imbalance prediction device for a distribution network based on digital twin is provided, and the three-phase imbalance prediction device for a distribution network based on digital twin comprises:

[0057] An acquisition module is used to obtain the node three-phase load state transfer probability and the three-phase load state transfer probability matrix of the distribution network at the current moment;

[0058] The first determination module is used to determine the state transfer probability distribution of the three-phase load of the node at the next moment of the distribution network based on the state transfer probability of the three-phase load of the node at the current moment of the distribution network and the three-phase load state transfer probability matrix;

[0059] The second determination module is used to determine the active power and reactive power of the node at the next moment of the distribution network based on the state transition probability distribution of the three-phase load of the node at the next moment of the distribution network;

[0060] A solution module, used for iteratively solving the three-phase current injected into the node of the distribution network at the next moment by using the active power and reactive power of the node of the distribution network at the next moment;

[0061] The prediction module is used to predict the three-phase imbalance degree of the node of the distribution network at the next moment based on the three-phase current injected into the node of the distribution network at the next moment.

[0062] In a third aspect, a storage device is provided, which stores a plurality of program codes, wherein the program codes are suitable for being loaded and run by a processor to execute the method for predicting three-phase imbalance of a distribution network based on digital twins as described in any of the above technical solutions.

[0063] In a fourth aspect, a control device is provided, which includes a processor and a storage device, wherein the storage device is suitable for storing multiple program codes, and the program codes are suitable for being loaded and run by the processor to execute the three-phase imbalance prediction method for the distribution network based on digital twins as described in any of the above technical solutions.

[0064] The above one or more technical solutions of the present invention have at least one or more of the following beneficial effects:

[0065] The present invention relates to the technical field of fault warning of distribution network, and specifically provides a method and device for predicting three-phase imbalance of distribution network based on digital twin, including: obtaining the state transfer probability of the three-phase load of the node at the current moment of the distribution network and the three-phase load state transfer probability matrix; determining the state transfer probability distribution of the three-phase load of the node at the next moment of the distribution network based on the state transfer probability of the three-phase load of the node at the current moment of the distribution network and the three-phase load state transfer probability matrix; determining the active power and reactive power of the node at the next moment of the distribution network based on the state transfer probability distribution of the three-phase load of the node at the next moment of the distribution network; iteratively solving the three-phase current injected into the node at the next moment of the distribution network by using the active power and reactive power of the node at the next moment of the distribution network; predicting the three-phase imbalance of the node at the next moment of the distribution network based on the three-phase current injected into the node at the next moment of the distribution network. Compared with the prior art, the scheme provided by the present invention fully considers the random characteristics of the distribution network user behavior, makes up for the defects of the prior art, can objectively and comprehensively predict the three-phase imbalance of the distribution network, and provides an effective reference basis for the analysis and management of the three-phase imbalance situation of the distribution network. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] Figure 1 It is a schematic flow chart of the main steps of a method for predicting three-phase imbalance of a distribution network based on digital twins according to an embodiment of the present invention;

[0067] Figure 2 This is a diagram of a distribution network structure in an embodiment of the present invention;

[0068] Figure 3 is a curve diagram of the maximum value of three-phase unbalance within 24 hours of the distribution network PCC node in an embodiment of the present invention;

[0069] Figure 4 It is the main structural block diagram of the distribution network three-phase imbalance prediction device based on digital twin in an embodiment of the present invention. DETAILED DESCRIPTION

[0070] The specific implementation modes of the present invention will be further described in detail below in conjunction with the accompanying drawings.

[0071] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution 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 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.

[0072] See attached Figure 1 , Figure 1 1 is a schematic flow chart of the main steps of the method for predicting three-phase imbalance of a distribution network based on digital twins according to an embodiment of the present invention. Figure 1 As shown, the method for predicting three-phase imbalance of a distribution network based on digital twin in an embodiment of the present invention mainly includes the following steps:

[0073] Step S101: Obtain the node three-phase load state transfer probability and the three-phase load state transfer probability matrix of the distribution network at the current moment;

[0074] Step S102: determining the state transition probability distribution of the three-phase load at the node of the distribution network at the next moment based on the state transition probability of the three-phase load at the node of the distribution network at the current moment and the three-phase load state transition probability matrix;

[0075] Step S103: determining the active power and reactive power of the node at the next moment of the distribution network based on the state transition probability distribution of the three-phase load at the node at the next moment of the distribution network;

[0076] Step S104: using the active power and reactive power of the nodes of the distribution network at the next moment to iteratively solve the three-phase current injected into the nodes of the distribution network at the next moment;

[0077] Step S105: predicting the three-phase imbalance degree of the nodes in the distribution network at the next moment based on the three-phase current injected into the nodes in the distribution network at the next moment.

[0078] In this embodiment, the current time is T r +Kt r , where T r is the current sampling time of the system, K is the preset time interval between the current sampling time of the system and the current moment, t r is the preset time interval.

[0079] In one embodiment, the calculation formula for the node three-phase load state transition probability of the distribution network at the current moment is as follows:

[0080]

[0081] The calculation formula of the node three-phase load state transfer probability matrix of the distribution network at the current moment is as follows:

[0082]

[0083] In the above formula, is the load state transition probability of phase φ at node i in the distribution network at the current moment, is the number of times that the number of devices turned on in phase φ of node i of the distribution network changes from x to y at the current moment. is the total number of changes in the number of devices turned on at the i-th node of the distribution network at the current moment, is the load state transfer probability matrix of the φ phase of the i-th node in the distribution network at the current moment, x, y∈[1,M], M is the total number of devices connected to the distribution network nodes, φ∈[a,b,c].

[0084] In one embodiment, the state transition probability distribution of the three-phase load at the node of the distribution network at the next moment is calculated as follows:

[0085]

[0086] In the above formula, is the state transition probability distribution of the φ-phase load of node i in the distribution network at the next moment, is the distribution network T r When the state transition probability distribution of the load of node i is is the load state transfer probability matrix of the phase i of the distribution network at the last moment, is the load state transition probability matrix of the i-node φ phase in the distribution network at K moments;

[0087] Among them, the distribution network T r The calculation formula for the state transition probability distribution of the φ-phase load of node i is as follows:

[0088]

[0089] In the above formula, is the distribution network T r When the power of the Mth connected device of node i is T r The probability of the power collected by the system when

[0090] In one embodiment, the calculation formula of the active power of the node at the next moment of the distribution network is as follows:

[0091]

[0092] The calculation formula of the reactive power of the node of the distribution network at the next moment is as follows:

[0093]

[0094] In the above formula, is the active power of phase φ of node i in the distribution network at the next moment, is the state transition probability distribution of the three-phase load at the node of the distribution network at the next moment The mathematical expectation, P eφm is the rated power of the mth device connected to the node φ of the distribution network i, is the φ-phase reactive power of node i in the distribution network at the next moment, is the power factor angle of the mth device connected to the node φ of the distribution network i.

[0095] In one embodiment, the iterative solution of the three-phase current injected into the node of the distribution network at the next moment by using the active power and reactive power of the node of the distribution network at the next moment includes:

[0096] Step 1: Initialize the three-phase voltage of node i of the 0th iteration distribution network to distribution network T r The three-phase voltage of node i collected by the system is initialized to k=0;

[0097] Step 2 determines the three-phase complex power of node i at the next moment of the distribution network based on the active power and reactive power of node i at the next moment of the distribution network;

[0098] Step 3 determines the three-phase current injected into the i node at the next moment of the k-th iteration distribution network based on the three-phase complex power of the i node at the next moment of the distribution network and the three-phase voltage of the i node at the k-th iteration distribution network;

[0099] Step 4: determine the branch current matrix of the k+1th iteration distribution network at the next moment by using the three-phase current injected by the i node at the next moment of the k-th iteration distribution network, and obtain the three-phase current injected by the i node at the next moment of the k+1th iteration distribution network from the branch current matrix of the k+1th iteration distribution network at the next moment;

[0100] Step 5: Determine the k+1th iteration distribution network node voltage matrix using the three-phase current injected into the i node of the k+1th iteration distribution network at the next moment, and obtain the three-phase voltage of the i node of the k+1th iteration distribution network from the k+1th iteration distribution network node voltage matrix;

[0101] Step 6 determines whether the absolute value of the difference between the three-phase voltage of the i node of the k+1th iteration distribution network and the three-phase voltage of the i node of the kth iteration distribution network is less than a preset value. If so, the three-phase current injected into the i node of the k+1th iteration distribution network at the next moment is used as the three-phase current injected into the node of the distribution network at the next moment, and the three-phase current injected into the node of the distribution network at the next moment is output. Otherwise, set k=k+1 and return to step 3.

[0102] In one embodiment, the calculation formula of the three-phase complex power of the node i at the next moment of the distribution network is as follows:

[0103]

[0104] In the above formula, is the complex power of phase φ of node i in the distribution network at the next moment, and j is an imaginary unit.

[0105] Furthermore, the calculation formula of the three-phase current injected into the node i at the next moment of the k-th iteration of the distribution network is as follows:

[0106]

[0107] In the above formula, is the three-phase current injected into node i at the next moment of the k-th iteration distribution network, are the A, B, and C phase currents injected into node i at the next moment of the k-th iteration of the distribution network, are the complex power of phases A, B, and C of node i in the distribution network at the next moment, They are the phase voltages of node A, B, and C at the next moment of the k-th iteration of the distribution network.

[0108] In one embodiment, the calculation formula of the branch current matrix of the k+1th iteration distribution network at the next moment is as follows:

[0109]

[0110] In the above formula, is the branch current matrix of the k+1th iteration distribution network at the next moment, A is the distribution network node branch association matrix, E A is the identity matrix, is the branch current matrix of the k-th iteration distribution network at the next moment, I (k) is the three-phase current vector injected into each node of the k-th iteration distribution network at the next moment, N is the total number of distribution network nodes;

[0111] Among them, the distribution network node branch association matrix A is a 3N×3N order square matrix, and its calculation formula is as follows:

[0112] A=[A ij ]

[0113] In the above formula, i,j∈[1,N], if the i node is related to the j node in the distribution network, and the direction of the i node is away from the j node, then A ij is a 3×3 unit matrix. If node i is related to node j in the distribution network and the direction of node i is toward node j, then A ij is a negative 3×3 unit matrix. If the i node and the j node in the distribution network are unrelated, then A ij is a 3×3 zero matrix.

[0114] In one embodiment, the calculation formula of the k+1th iteration distribution network node voltage matrix is ​​as follows:

[0115]

[0116] In the above formula, U (k+1) is the k+1th iteration distribution network node voltage matrix, U s is the three-phase voltage of the bus node at the grid connection point, U (k) is the kth iteration distribution network node voltage matrix, ZL is the distribution network impedance matrix;

[0117] The calculation formula of the distribution network impedance matrix is ​​as follows:

[0118]

[0119] In the above formula, Z iAA , Z iBB , Z iCC are the self-impedances of phases A, B, and C at node i in the distribution network, and Z iAB , Z iBC , Z iCA are the mutual impedances of nodes AB, BC, and CA in the distribution network, respectively, and Z iAB =Z iBA , Z iBC =Z iCB , Z iCA =Z iAC .

[0120] In this embodiment, the calculation formula for the three-phase unbalance degree of the node of the distribution network at the next moment is as follows:

[0121]

[0122] In the above formula, is the three-phase unbalance degree of node i in the distribution network at the next moment, They are respectively the A, B, and C phase currents injected into node i of the distribution network at the next moment.

[0123] Based on the above method, the present invention provides an optimal implementation method, and the present application embodiment is studied in combination with an actual distribution network system. Figure 2 As shown in Figure 1, the transformer capacity is 100kVA. The distribution network contains 24 load nodes, each of which is connected to 3 to 6 single-phase residential users. The distribution line model is JKLY-10 / 10, and the line length parameters between each node are shown in Table 1. In the calculation process of the three-phase unbalance prediction value, Tr is taken as 15min, t r Take 0.5min.

[0124] Table 1 Line parameters between nodes in the distribution network

[0125]

[0126]

[0127] The distribution network includes a total of 114 households. Figure 3 It is the maximum value data of three-phase unbalance in the Tr time period of 24 hours predicted by the PCC node location. Figure 3It can be seen that the three-phase imbalance is affected by the user's electricity consumption behavior during the day and is volatile. The larger fluctuations mainly occur when residents use electricity intensively, such as around 8 am, around 12 noon, and around 18 pm. The fluctuation trend of the three-phase imbalance shows that the established simulation model can reflect the actual situation to a certain extent.

[0128] Based on the same inventive concept, the present invention provides a three-phase imbalance prediction device for a distribution network based on digital twins, such as Figure 4 As shown, the distribution network three-phase imbalance prediction device based on digital twin includes:

[0129] An acquisition module is used to obtain the node three-phase load state transfer probability and the three-phase load state transfer probability matrix of the distribution network at the current moment;

[0130] The first determination module is used to determine the state transfer probability distribution of the three-phase load of the node at the next moment of the distribution network based on the state transfer probability of the three-phase load of the node at the current moment of the distribution network and the three-phase load state transfer probability matrix;

[0131] The second determination module is used to determine the active power and reactive power of the node at the next moment of the distribution network based on the state transition probability distribution of the three-phase load of the node at the next moment of the distribution network;

[0132] A solution module, used for iteratively solving the three-phase current injected into the node of the distribution network at the next moment by using the active power and reactive power of the node of the distribution network at the next moment;

[0133] The prediction module is used to predict the three-phase imbalance degree of the node of the distribution network at the next moment based on the three-phase current injected into the node of the distribution network at the next moment.

[0134] Preferably, the current time is T r +Kt r , where T r is the current sampling time of the system, K is the preset time interval between the current sampling time of the system and the current moment, t r is the preset time interval.

[0135] Furthermore, the calculation formula for the node three-phase load state transition probability of the distribution network at the current moment is as follows:

[0136]

[0137] The calculation formula of the node three-phase load state transfer probability matrix of the distribution network at the current moment is as follows:

[0138]

[0139] In the above formula, is the load state transition probability of phase φ at node i in the distribution network at the current moment, is the number of times that the number of devices turned on in phase φ of node i of the distribution network changes from x to y at the current moment. is the total number of changes in the number of devices turned on at the i-th node of the distribution network at the current moment, is the load state transfer probability matrix of the φ phase of the i-th node in the distribution network at the current moment, x, y∈[1,M], M is the total number of devices connected to the distribution network nodes, φ∈[a,b,c].

[0140] Furthermore, the calculation formula for the state transition probability distribution of the three-phase load of the node in the distribution network at the next moment is as follows:

[0141]

[0142] In the above formula, is the state transition probability distribution of the φ-phase load of node i in the distribution network at the next moment, is the distribution network T r When the state transition probability distribution of the load of node i is is the load state transfer probability matrix of the phase i of the distribution network at the last moment, is the load state transition probability matrix of the i-node φ phase in the distribution network at K moments;

[0143] Among them, the distribution network T r The calculation formula for the state transition probability distribution of the φ-phase load of node i is as follows:

[0144]

[0145] In the above formula, is the distribution network T r When the power of the Mth connected device of node i is T r The probability of the power collected by the system when

[0146] Furthermore, the calculation formula of the active power of the node of the distribution network at the next moment is as follows:

[0147]

[0148] The calculation formula of the reactive power of the node of the distribution network at the next moment is as follows:

[0149]

[0150] In the above formula, is the active power of phase φ of node i in the distribution network at the next moment, is the state transition probability distribution of the three-phase load at the node of the distribution network at the next moment The mathematical expectation, Peφm is the rated power of the mth device connected to the node φ of the distribution network i, is the φ-phase reactive power of node i in the distribution network at the next moment, is the power factor angle of the mth device connected to the node φ of the distribution network i.

[0151] Furthermore, the method of iteratively solving the three-phase current injected into the node of the distribution network at the next moment by using the active power and reactive power of the node of the distribution network at the next moment includes:

[0152] Step 1: Initialize the three-phase voltage of node i of the 0th iteration distribution network to distribution network T r The three-phase voltage of node i collected by the system is initialized to k=0;

[0153] Step 2 determines the three-phase complex power of node i at the next moment of the distribution network based on the active power and reactive power of node i at the next moment of the distribution network;

[0154] Step 3 determines the three-phase current injected into the i node at the next moment of the k-th iteration distribution network based on the three-phase complex power of the i node at the next moment of the distribution network and the three-phase voltage of the i node at the k-th iteration distribution network;

[0155] Step 4: determine the branch current matrix of the k+1th iteration distribution network at the next moment by using the three-phase current injected by the i node at the next moment of the k-th iteration distribution network, and obtain the three-phase current injected by the i node at the next moment of the k+1th iteration distribution network from the branch current matrix of the k+1th iteration distribution network at the next moment;

[0156] Step 5: Determine the k+1th iteration distribution network node voltage matrix using the three-phase current injected into the i node of the k+1th iteration distribution network at the next moment, and obtain the three-phase voltage of the i node of the k+1th iteration distribution network from the k+1th iteration distribution network node voltage matrix;

[0157] Step 6 determines whether the absolute value of the difference between the three-phase voltage of the i node of the k+1th iteration distribution network and the three-phase voltage of the i node of the kth iteration distribution network is less than a preset value. If so, the three-phase current injected into the i node of the k+1th iteration distribution network at the next moment is used as the three-phase current injected into the node of the distribution network at the next moment, and the three-phase current injected into the node of the distribution network at the next moment is output. Otherwise, set k=k+1 and return to step 3.

[0158] Furthermore, the calculation formula of the three-phase complex power of the node i at the next moment of the distribution network is as follows:

[0159]

[0160] In the above formula, is the complex power of phase φ of node i in the distribution network at the next moment, and j is an imaginary unit.

[0161] Furthermore, the calculation formula of the three-phase current injected into the node i at the next moment of the k-th iteration of the distribution network is as follows:

[0162]

[0163] In the above formula, is the three-phase current injected into node i at the next moment of the k-th iteration distribution network, are the A, B, and C phase currents injected into node i at the next moment of the k-th iteration of the distribution network, are the complex power of phases A, B, and C of node i in the distribution network at the next moment, They are the phase voltages of node A, B, and C at the next moment of the k-th iteration of the distribution network.

[0164] Furthermore, the calculation formula of the branch current matrix of the distribution network at the next moment of the k+1th iteration is as follows:

[0165]

[0166] In the above formula, is the branch current matrix of the k+1th iteration distribution network at the next moment, A is the distribution network node branch association matrix, E A is the identity matrix, is the branch current matrix of the k-th iteration distribution network at the next moment, I (k) is the three-phase current vector injected into each node of the k-th iteration distribution network at the next moment, N is the total number of distribution network nodes;

[0167] Among them, the distribution network node branch association matrix A is a 3N×3N order square matrix, and its calculation formula is as follows:

[0168] A=[A ij ]

[0169] In the above formula, i,j∈[1,N], if the i node is related to the j node in the distribution network, and the direction of the i node is away from the j node, then A ij is a 3×3 unit matrix. If node i is related to node j in the distribution network and the direction of node i is toward node j, then A ij is a negative 3×3 unit matrix. If the i node and the j node in the distribution network are unrelated, then A ij is a 3×3 zero matrix.

[0170] Furthermore, the calculation formula of the k+1th iteration distribution network node voltage matrix is ​​as follows:

[0171]

[0172] In the above formula, U (k+1) is the k+1th iteration distribution network node voltage matrix, U s is the three-phase voltage of the bus node at the grid connection point, U (k) is the kth iteration distribution network node voltage matrix, Z L is the distribution network impedance matrix;

[0173] The calculation formula of the distribution network impedance matrix is ​​as follows:

[0174]

[0175] In the above formula, Z iAA , Z iBB , Z iCC are the self-impedances of phases A, B, and C at node i in the distribution network, and Z iAB , Z iBC , Z iCA are the mutual impedances of nodes AB, BC, and CA in the distribution network, respectively, and Z iAB =Z iBA , Z iBC =Z iCB , Z iCA =Z iAC .

[0176] Preferably, the calculation formula of the three-phase unbalance degree of the node of the distribution network at the next moment is as follows:

[0177]

[0178] In the above formula, is the three-phase unbalance degree of node i in the distribution network at the next moment, They are respectively the A, B, and C phase currents injected into node i of the distribution network at the next moment.

[0179] Furthermore, the present invention provides a storage device storing a plurality of program codes, wherein the program codes are suitable for being loaded and run by a processor to execute the three-phase imbalance prediction method for distribution network based on digital twin as described in any of the above technical solutions.

[0180] Furthermore, the present invention provides a control device, which includes a processor and a storage device, wherein the storage device is suitable for storing multiple program codes, and the program codes are suitable for being loaded and run by the processor to execute the three-phase imbalance prediction method for the distribution network based on digital twins described in any of the above technical solutions.

[0181] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0182] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0183] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0184] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0185] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A method for predicting three-phase imbalance of distribution network based on digital twin, characterized in that: The method comprises: Obtain the node three-phase load state transfer probability and three-phase load state transfer probability matrix of the distribution network at the current moment; Determine the state transition probability distribution of the three-phase load at the node of the distribution network at the next moment based on the state transition probability of the three-phase load at the node of the distribution network at the current moment and the three-phase load state transition probability matrix; Determine the active power and reactive power of the nodes in the distribution network at the next moment based on the state transition probability distribution of the three-phase load of the nodes in the distribution network at the next moment; The three-phase current injected into the node of the distribution network at the next moment is iteratively solved by using the active power and reactive power of the node of the distribution network at the next moment; Predict the three-phase unbalance degree of the node in the distribution network at the next moment based on the three-phase current injected into the node at the next moment; The current time is T r +Kt r , where T r is the current sampling time of the system, K is the preset time interval between the current sampling time of the system and the current moment, t r is a preset time interval; The calculation formula of the node three-phase load state transfer probability of the distribution network at the current moment is as follows: The calculation formula of the node three-phase load state transfer probability matrix of the distribution network at the current moment is as follows: In the above formula, is the load state transition probability of phase φ at node i in the distribution network at the current moment, is the number of times that the number of devices turned on in phase φ of node i of the distribution network changes from x to y at the current moment. is the total number of changes in the number of devices turned on at the i-th node of the distribution network at the current moment, is the load state transfer probability matrix of the phase φ of the i-node of the distribution network at the current moment, x, y∈[1,M], M is the total number of devices connected to the distribution network node, φ∈[a,b,c]; The calculation formula for the state transition probability distribution of the three-phase load at the node of the distribution network at the next moment is as follows: In the above formula, is the state transition probability distribution of the φ-phase load of node i in the distribution network at the next moment, is the distribution network T r When the state transition probability distribution of the load of node i is is the load state transfer probability matrix of the phase i of the distribution network at the last moment, is the load state transition probability matrix of the i-node φ phase in the distribution network at K moments; Among them, the distribution network T r The calculation formula for the state transition probability distribution of the φ-phase load of node i is as follows: In the above formula, is the distribution network T r When the power of the Mth connected device of node i is T r The probability of the power collected by the system when The calculation formula of the active power of the node at the next moment of the distribution network is as follows: The calculation formula of the reactive power of the node of the distribution network at the next moment is as follows: In the above formula, is the φ-phase active power of node i in the distribution network at the next moment, is the state transition probability distribution of the three-phase load at the node of the distribution network at the next moment The mathematical expectation, P eφm is the rated power of the mth device connected to the node φ of the distribution network i, is the φ-phase reactive power of node i in the distribution network at the next moment, is the power factor angle of the mth device connected to the node φ of the distribution network i.

2. The method according to claim 1, characterized in that The method of iteratively solving the three-phase current injected into the node of the distribution network at the next moment by using the active power and reactive power of the node of the distribution network at the next moment comprises: Step 1: Initialize the three-phase voltage of node i of the 0th iteration distribution network to distribution network T r The three-phase voltage of node i collected by the system is initialized to k=0; Step 2 determines the three-phase complex power of node i at the next moment of the distribution network based on the active power and reactive power of node i at the next moment of the distribution network; Step 3 determines the three-phase current injected into the i node at the next moment of the k-th iteration distribution network based on the three-phase complex power of the i node at the next moment of the distribution network and the three-phase voltage of the i node at the k-th iteration distribution network; Step 4: determine the branch current matrix of the k+1th iteration distribution network at the next moment by using the three-phase current injected by the i node at the next moment of the k-th iteration distribution network, and obtain the three-phase current injected by the i node at the next moment of the k+1th iteration distribution network from the branch current matrix of the k+1th iteration distribution network at the next moment; Step 5: Determine the k+1th iteration distribution network node voltage matrix using the three-phase current injected into the i node of the k+1th iteration distribution network at the next moment, and obtain the three-phase voltage of the i node of the k+1th iteration distribution network from the k+1th iteration distribution network node voltage matrix; Step 6 determines whether the absolute value of the difference between the three-phase voltage of the i node of the k+1th iteration distribution network and the three-phase voltage of the i node of the kth iteration distribution network is less than a preset value. If so, the three-phase current injected into the i node of the k+1th iteration distribution network at the next moment is used as the three-phase current injected into the node of the distribution network at the next moment, and the three-phase current injected into the node of the distribution network at the next moment is output. Otherwise, set k=k+1 and return to step 3.

3. The method according to claim 2, characterized in that The calculation formula of the three-phase complex power of node i in the distribution network at the next moment is as follows: In the above formula, is the complex power of phase φ of node i in the distribution network at the next moment, and j is an imaginary unit.

4. The method according to claim 2, characterized in that The calculation formula of the three-phase current injected into the node i at the next moment of the k-th iteration distribution network is as follows: In the above formula, is the three-phase current injected into node i at the next moment of the k-th iteration distribution network, are the A, B, and C phase currents injected into node i at the next moment of the k-th iteration of the distribution network, are the complex power of phases A, B, and C of node i in the distribution network at the next moment, They are the phase voltages of node A, B, and C at the next moment of the k-th iteration of the distribution network.

5. The method according to claim 4, characterized in that The calculation formula of the branch current matrix of the k+1th iteration distribution network at the next moment is as follows: In the above formula, is the branch current matrix of the k+1th iteration distribution network at the next moment, A is the distribution network node branch association matrix, E A is the identity matrix, is the branch current matrix of the k-th iteration distribution network at the next moment, I (k) is the three-phase current vector injected into each node of the k-th iteration distribution network at the next moment, N is the total number of distribution network nodes; Among them, the distribution network node branch association matrix A is a 3N×3N order square matrix, and its calculation formula is as follows: A=[A ij ] In the above formula, i,j∈[1,N], if the i node is related to the j node in the distribution network, and the direction of the i node is away from the j node, then A ij is a 3×3 unit matrix. If node i is related to node j in the distribution network and the direction of node i is toward node j, then A ij is a negative 3×3 unit matrix. If the i node and the j node in the distribution network are unrelated, then A ij is a 3×3 zero matrix.

6. The method according to claim 5, characterized in that The calculation formula of the k+1th iteration distribution network node voltage matrix is ​​as follows: In the above formula, U (k+1) is the k+1th iteration distribution network node voltage matrix, U s is the three-phase voltage of the bus node at the grid connection point, U (k) is the kth iteration distribution network node voltage matrix, Z L is the distribution network impedance matrix; The calculation formula of the distribution network impedance matrix is ​​as follows: In the above formula, Z iAA , Z iBB , Z iCC are the self-impedances of phases A, B, and C at node i in the distribution network, and Z iAB , Z iBC , Z iCA are the mutual impedances of nodes AB, BC, and CA in the distribution network, respectively, and Z iAB =Z iBA , Z iBC =Z iCB , Z iCA =Z iAC .

7. The method according to claim 1, characterized in that The calculation formula of the three-phase unbalance degree of the node of the distribution network at the next moment is as follows: In the above formula, is the three-phase unbalance degree of node i in the distribution network at the next moment, They are respectively the A, B, and C phase currents injected into node i of the distribution network at the next moment.

8. A device for predicting the three-phase imbalance of a distribution network based on digital twins according to any one of claims 1 to 7, characterized in that: The device comprises: An acquisition module is used to obtain the node three-phase load state transfer probability and the three-phase load state transfer probability matrix of the distribution network at the current moment; The first determination module is used to determine the state transfer probability distribution of the three-phase load of the node at the next moment of the distribution network based on the state transfer probability of the three-phase load of the node at the current moment of the distribution network and the three-phase load state transfer probability matrix; The second determination module is used to determine the active power and reactive power of the node at the next moment of the distribution network based on the state transition probability distribution of the three-phase load at the node at the next moment of the distribution network; A solution module, used for iteratively solving the three-phase current injected into the node of the distribution network at the next moment by using the active power and reactive power of the node of the distribution network at the next moment; The prediction module is used to predict the three-phase imbalance degree of the node of the distribution network at the next moment based on the three-phase current injected into the node of the distribution network at the next moment.

9. A storage device storing a plurality of program codes, characterized in that: The program code is suitable for being loaded and run by a processor to execute the distribution network three-phase imbalance prediction method based on digital twin according to any one of claims 1 to 7.

10. A control device, comprising a processor and a storage device, wherein the storage device is suitable for storing a plurality of program codes, characterized in that: The program code is suitable for being loaded and run by the processor to execute the distribution network three-phase imbalance prediction method based on digital twin according to any one of claims 1 to 7.

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