Fault recovery method and device for alternating-current and direct-current hybrid power distribution network

Abstract

The invention relates to the technical field of distribution network fault isolation, and particularly provides an AC / DC hybrid power distribution network fault recovery method and device, and the method comprises the steps: carrying out the fuzzy opportunity constraint relaxation and second-order cone relaxation of a fault recovery model corresponding to an AC / DC hybrid power distribution network, and obtaining a to-be-solved fault recovery model; solving the to-be-solved fault recovery model to obtain an optimization result; and based on the optimization result, obtaining a fault recovery scheme of the AC / DC hybrid power distribution network, and performing fault recovery on the AC / DC hybrid power distribution network by using the fault recovery scheme of the AC / DC hybrid power distribution network. Wherein the optimization result comprises at least one of a node power-on state and a line on-off state. According to the technical scheme provided by the invention, the load recovery proportion can be effectively increased, the fault recovery capability of the power distribution network is enhanced, the voltage quality can be effectively improved, and the voltage out-of-limit risk is reduced.

Description

Technical Field

[0001] This invention relates to the field of distribution network fault isolation technology, specifically to a method and apparatus for fault recovery in AC / DC hybrid distribution networks. Background Technology

[0002] Distributed power sources (DPS) are rapidly gaining popularity due to their environmental friendliness, cleanliness, and sustainability. However, traditional AC distribution networks face challenges such as increased network losses and reduced operational efficiency when large-scale DPS integration occurs, while the comprehensive construction of DC distribution networks would impose a significant economic burden. In contrast, hybrid AC / DC distribution networks combine the advantages of both AC and DC networks, offering lower construction costs and high operational efficiency, making them an important direction for distribution network development. The network architecture of hybrid AC / DC distribution networks differs from that of traditional distribution networks, and the process of constructing fault recovery models becomes more complex under the influence of DPS, primarily due to changes in the Jacobian matrix dimension and the need to properly handle the uncertainty of DPS output. Therefore, researching fault recovery methods for hybrid AC / DC distribution networks adapted to distributed resource integration is crucial for ensuring their safe operation.

[0003] However, current research lacks consideration of the uncertainty in the output of distributed generation sources. Distributed generation sources, such as wind and solar power, exhibit strong randomness and volatility, with their output affected by various factors such as weather conditions and seasonal changes, resulting in significant uncertainty. This uncertainty can easily lead to dimensionality-curse problems in the fault recovery models of AC / DC hybrid distribution networks, making it difficult to obtain the optimal load recovery scheme. Summary of the Invention

[0004] To overcome the above-mentioned defects, this invention proposes a method and apparatus for fault recovery in AC / DC hybrid distribution networks.

[0005] Firstly, a fault recovery method for an AC / DC hybrid distribution network is provided, the method comprising:

[0006] Fuzzy chance constraint relaxation and second-order cone relaxation are applied to the fault recovery model corresponding to the AC / DC hybrid distribution network to obtain the fault recovery model to be solved.

[0007] The fault recovery model to be solved is then solved to obtain the optimization results;

[0008] Based on the optimization results, a fault recovery scheme for AC / DC hybrid distribution network is obtained, and the AC / DC hybrid distribution network fault recovery scheme is used to perform fault recovery on the AC / DC hybrid distribution network.

[0009] The optimization results include at least one of the following: node power-on status and line on / off status.

[0010] Preferably, the fault recovery model includes: an objective function and its corresponding constraints aimed at minimizing the weighted load loss and network power loss of the AC / DC hybrid distribution network.

[0011] Furthermore, the objective function is as follows:

[0012] min(C LOAD +P loss )

[0013] In the above formula, C LOAD For the weighted load loss of the AC / DC hybrid distribution network, P loss This refers to the power loss of the AC / DC hybrid distribution network.

[0014] Furthermore, the weighted load loss of the AC / DC hybrid distribution network is as follows:

[0015]

[0016] The power loss of the AC / DC hybrid distribution network is as follows:

[0017]

[0018] In the above formula, Let N be the active load of the i-th node in time period t. T Let w be the total number of fault time intervals, N be the total number of nodes, and w be the total number of fault time intervals. i Let y be the weighting coefficient for the load of the i-th node. i The variable is 0-1, representing the power-on state of node i, where 0 indicates power off and 1 indicates power on. ac For the collection of AC lines, L dc For a collection of DC lines, I l,t R is the current in branch l. l Let be the resistance of branch l.

[0019] Furthermore, the constraints include: power balance constraints, maintenance constraints, connectivity and radial constraints, and voltage and current constraints.

[0020] Furthermore, the power balance constraint is as follows:

[0021]

[0022] The maintenance constraints are as follows:

[0023]

[0024] The connectivity and radial constraints are as follows:

[0025]

[0026] The voltage and current constraints are as follows:

[0027]

[0028] In the above formula, Ω acb For the set of AC branches, Ω dcb Let P be a set of DC lines, where l(j,:) represents a branch l starting at node j, and l(:,j) represents a branch l ending at node j. l,t Q l,t These represent the active power and reactive power of branch l during time period t, respectively, R. l and X l The resistance and reactance of branch l are respectively, and y i,t The variable is 0-1, representing the power supply status of node i during time period t, where 0 indicates power failure and 1 indicates power supply. j,t The variable is 0-1, representing the power supply status of node j during time period t, where 0 indicates power failure and 1 indicates power supply. This represents the replacement of the squared voltage variable at node j during time period t. This represents the replacement of the squared voltage variable at node i during time period t. This represents the substitution of the squared current variable in branch l during time period t. To represent the substitution of the squared active power variable at node i in time period t, To represent the substitution of the squared reactive power variable at node i during time period t. Let be the active power of the conventional generating units at node j during time period t. Let be the active power of the distributed power source at node j during time period t. Let be the energy storage discharge power of node j during time period t. Let be the energy storage charging power of node j during time period t. Let t be the active load of node j in time period t. Let t be the reactive power of the conventional generating units at node j during time period t. Y represents the reactive load of node j during time period t. ij Let t be a 0-1 variable representing the on / off state of line ij, F be the set of all faulty lines in the distribution network, and t be a variable representing the on / off state of line ij. m t n The time during the fault period, For t m The on / off state of line ij at time 1. For t n The on / off state of line ij at time 1. For t m +T f The on / off status of line ij during the time period, T fThe time required to repair one line, K is the maximum number of lines that can be repaired simultaneously within a time period, and F is the time required to repair one line. jk,t F represents the virtual power of the line between node j and node k during time period t. ij,t Let L represent the virtual power of the line between node i and node j during time period t, DG be the set of distributed power generation nodes, l(j,k) be the set of lines for line jk, and l(i,j) be the set of lines for line ij. j,t This represents the power provided by the source node in the virtual network during time period t, where M is a constant and N is a variable. DG Indicates the number of distributed power sources. and These are the squares of the upper and lower limits of the node voltage, respectively. Y is the square of the maximum allowable current of the branch. ij,t The on / off status of line ij during time period t.

[0029] Furthermore, the fault recovery model corresponding to the AC / DC hybrid distribution network is subjected to fuzzy chance constraint relaxation and second-order cone relaxation to obtain the fault recovery model to be solved, including:

[0030] Regarding the and Perform fuzzy chance constraint relaxation to obtain fuzzy chance relaxation constraints, and then use the fuzzy chance relaxation constraints to apply the following to the... and Replace;

[0031] Regarding the and Perform second-order cone relaxation to obtain second-order cone relaxation constraints, and use the second-order cone relaxation constraints to apply to the... and Replace it.

[0032] Furthermore, the fuzzy chance relaxation constraint is as follows:

[0033]

[0034] The second-order cone relaxation constraint is as follows:

[0035]

[0036] In the above formula, α is the confidence level, and P WT,t,1 P WT,t,2 P represents the first and second membership parameters of the fan. PV,t,1 P PV,t,2 These are the first and second membership parameters for photovoltaics.

[0037] Secondly, a fault recovery device for a hybrid AC / DC distribution network is provided, the hybrid AC / DC distribution network fault recovery device comprising:

[0038] The conversion module is used to perform fuzzy chance constraint relaxation and second-order cone relaxation on the fault recovery model corresponding to the AC / DC hybrid distribution network to obtain the fault recovery model to be solved.

[0039] The analysis module is used to solve the fault recovery model to be solved and obtain the optimization results;

[0040] The recovery module is used to obtain a fault recovery scheme for the AC / DC hybrid distribution network based on the optimization results, and to perform fault recovery on the AC / DC hybrid distribution network using the AC / DC hybrid distribution network fault recovery scheme;

[0041] The optimization results include at least one of the following: node power-on status and line on / off status.

[0042] Preferably, the fault recovery model includes: an objective function and its corresponding constraints aimed at minimizing the weighted load loss and network power loss of the AC / DC hybrid distribution network.

[0043] Furthermore, the objective function is as follows:

[0044] min(C LOAD +P loss )

[0045] In the above formula, C LOAD For the weighted load loss of the AC / DC hybrid distribution network, P loss This refers to the power loss of the AC / DC hybrid distribution network.

[0046] Furthermore, the weighted load loss of the AC / DC hybrid distribution network is as follows:

[0047]

[0048] The power loss of the AC / DC hybrid distribution network is as follows:

[0049]

[0050] In the above formula, Let N be the active load of the i-th node in time period t. T Let w be the total number of fault time intervals, N be the total number of nodes, and w be the total number of fault time intervals. i Let y be the weighting coefficient for the load of the i-th node. i The variable is 0-1, representing the power-on state of node i, where 0 indicates power off and 1 indicates power on. ac For the collection of AC lines, L dc For a collection of DC lines, I l,t R is the current in branch l. l Let be the resistance of branch l.

[0051] Furthermore, the constraints include: power balance constraints, maintenance constraints, connectivity and radial constraints, and voltage and current constraints.

[0052] Furthermore, the power balance constraint is as follows:

[0053]

[0054] The maintenance constraints are as follows:

[0055]

[0056] The connectivity and radial constraints are as follows:

[0057]

[0058] The voltage and current constraints are as follows:

[0059]

[0060] In the above formula, Ω acb For the set of AC branches, Ω dcb Let P be a set of DC lines, where l(j,:) represents a branch l starting at node j, and l(:,j) represents a branch l ending at node j. l,t Q l,t These represent the active power and reactive power of branch l during time period t, respectively, R. l and X l The resistance and reactance of branch l are respectively, and y i,t The variable is 0-1, representing the power supply status of node i during time period t, where 0 indicates power failure and 1 indicates power supply. j,t The variable is 0-1, representing the power supply status of node j during time period t, where 0 indicates power failure and 1 indicates power supply. This represents the replacement of the squared voltage variable at node j during time period t. This represents the replacement of the squared voltage variable at node i during time period t. This represents the substitution of the squared current variable in branch l during time period t. To represent the substitution of the squared active power variable at node i in time period t, To represent the substitution of the squared reactive power variable at node i during time period t. Let be the active power of the conventional generating units at node j during time period t. Let be the active power of the distributed power source at node j during time period t. Let be the energy storage discharge power of node j during time period t. Let be the energy storage charging power of node j during time period t. Let t be the active load of node j in time period t. Let t be the reactive power of the conventional generating units at node j during time period t. Y represents the reactive load of node j during time period t. ij Let t be a 0-1 variable representing the on / off state of line ij, F be the set of all faulty lines in the distribution network, and t be a variable representing the on / off state of line ij. m t n The time during the fault period, For t m The on / off state of line ij at time 1. For t n The on / off state of line ij at time 1. For t m +T f The on / off status of line ij during the time period, T f The time required to repair one line, K is the maximum number of lines that can be repaired simultaneously within a time period, and F is the time required to repair one line. jk,t F represents the virtual power of the line between node j and node k during time period t. ij,t Let L represent the virtual power of the line between node i and node j during time period t, DG be the set of distributed power generation nodes, l(j,k) be the set of lines for line jk, and l(i,j) be the set of lines for line ij. j,t This represents the power provided by the source node in the virtual network during time period t, where M is a constant and N is a variable. DG Indicates the number of distributed power sources. and These are the squares of the upper and lower limits of the node voltage, respectively. Y is the square of the maximum allowable current of the branch. ij,t The on / off status of line ij during time period t.

[0061] Furthermore, the conversion module is specifically used for:

[0062] Regarding the and Perform fuzzy chance constraint relaxation to obtain fuzzy chance relaxation constraints, and then use the fuzzy chance relaxation constraints to apply the following to the... and Replace;

[0063] Regarding the and Perform second-order cone relaxation to obtain second-order cone relaxation constraints, and use the second-order cone relaxation constraints to apply to the... and Replace it.

[0064] Furthermore, the fuzzy chance relaxation constraint is as follows:

[0065]

[0066] The second-order cone relaxation constraint is as follows:

[0067]

[0068] In the above formula, α is the confidence level, and P WT,t,1 P WT,t,2 P represents the first and second membership parameters of the fan. PV,t,1 P PV,t,2 These are the first and second membership parameters for photovoltaics.

[0069] Thirdly, a computer device is provided, comprising: one or more processors;

[0070] The processor is used to execute one or more programs;

[0071] When the one or more programs are executed by the one or more processors, the AC / DC hybrid power distribution network fault recovery method is implemented.

[0072] Fourthly, a computer-readable storage medium is provided having a computer program stored thereon, wherein when the computer program is executed, the method for fault recovery of the AC / DC hybrid distribution network is implemented.

[0073] The above-described technical solutions of the present invention have at least one or more of the following beneficial effects:

[0074] This invention provides a method and apparatus for fault recovery in AC / DC hybrid distribution networks, comprising: performing fuzzy opportunistic constraint relaxation and second-order cone relaxation on a fault recovery model corresponding to the AC / DC hybrid distribution network to obtain a fault recovery model to be solved; solving the fault recovery model to be solved to obtain an optimization result; obtaining a fault recovery scheme for the AC / DC hybrid distribution network based on the optimization result, and using the AC / DC hybrid distribution network fault recovery scheme to perform fault recovery on the AC / DC hybrid distribution network; wherein, the optimization result includes at least one of the following: node energization status and line on / off status. This invention relaxes constraints on fuzzy opportunistic constraints and nonlinear constraints, transforming the optimization model into a convex problem, which can effectively handle the uncertainty of distributed power generation output. Then, the problem is solved, and the optimal fault recovery scheme under the uncertainty of distributed power generation is obtained, minimizing the fault recovery cost while considering risk controllability. This effectively improves the load recovery ratio, enhances the fault recovery capability of the distribution network, and effectively improves voltage quality and reduces the risk of voltage exceeding limits. Attached Figure Description

[0075] Figure 1 This is a schematic flowchart of the main steps of the AC / DC hybrid distribution network fault recovery method according to an embodiment of the present invention;

[0076] Figure 2This is a schematic diagram of a fault in an AC / DC hybrid distribution network according to an embodiment of the present invention;

[0077] Figure 3 This is a recovery result diagram for the 9:00-10:00 time period according to an embodiment of the present invention;

[0078] Figure 4 This is a recovery result diagram for the 10:00-11:00 time period according to an embodiment of the present invention;

[0079] Figure 5 This is a recovery result diagram for the 11:00-12:00 time period according to an embodiment of the present invention;

[0080] Figure 6 This is a recovery result diagram for the 12:00-13:00 time period according to an embodiment of the present invention;

[0081] Figure 7 This is a graph showing the node voltage fluctuation during different fault periods according to an embodiment of the present invention. Detailed Implementation

[0082] The specific embodiments of the present invention will be further described in detail below with reference to the accompanying drawings.

[0083] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0084] As disclosed in the background section, distributed generation (DG) has seen rapid growth in penetration due to its advantages such as environmental friendliness, cleanliness, and sustainability. However, with the large-scale integration of DG, traditional AC distribution networks face problems such as increased network losses and reduced operating efficiency, while the comprehensive construction of DC distribution networks would impose a significant economic burden. In contrast, hybrid AC / DC distribution networks combine the advantages of both AC and DC distribution networks, offering lower construction costs and high operational efficiency, and have become an important direction for distribution network development. The network architecture of hybrid AC / DC distribution networks differs from that of traditional distribution networks, and the process of constructing their fault recovery models becomes more complex under the influence of DG, mainly due to changes in the Jacobian matrix dimension and the need to properly handle the uncertainty of DG output. Therefore, researching fault recovery methods for hybrid AC / DC distribution networks adapted to distributed resource integration is of great significance for ensuring their safe operation.

[0085] However, current research lacks consideration of the uncertainty in the output of distributed generation sources. Distributed generation sources, such as wind and solar power, exhibit strong randomness and volatility, with their output affected by various factors such as weather conditions and seasonal changes, resulting in significant uncertainty. This uncertainty can easily lead to dimensionality-curse problems in the fault recovery models of AC / DC hybrid distribution networks, making it difficult to obtain the optimal load recovery scheme.

[0086] To address the aforementioned problems, this invention provides a method and apparatus for fault recovery in AC / DC hybrid distribution networks. The method includes: performing fuzzy opportunistic constraint relaxation and second-order cone relaxation on a fault recovery model corresponding to the AC / DC hybrid distribution network to obtain a fault recovery model to be solved; solving the fault recovery model to obtain an optimization result; obtaining a fault recovery scheme for the AC / DC hybrid distribution network based on the optimization result; and using the AC / DC hybrid distribution network fault recovery scheme to perform fault recovery on the AC / DC hybrid distribution network. The optimization result includes at least one of the following: node energization status and line on / off status. This invention relaxes constraints on fuzzy opportunistic and nonlinear constraints, transforming the optimization model into a convex problem. This effectively handles the uncertainty of distributed power generation output. The problem is then solved, and the optimal fault recovery scheme under the uncertainty of distributed power generation is obtained, minimizing fault recovery costs while ensuring risk controllability. This effectively increases the load recovery ratio, enhances the fault recovery capability of the distribution network, and simultaneously improves voltage quality and reduces the risk of voltage exceeding limits.

[0087] The above plan will be explained in detail below.

[0088] Example 1

[0089] See appendix Figure 1 , Figure 1 This is a schematic flowchart illustrating the main steps of a hybrid AC / DC distribution network fault recovery method according to an embodiment of the present invention. Figure 1 As shown, the AC / DC hybrid distribution network fault recovery method in this embodiment of the invention mainly includes the following steps:

[0090] Step S101: Perform fuzzy chance constraint relaxation and second-order cone relaxation on the fault recovery model corresponding to the AC / DC hybrid distribution network to obtain the fault recovery model to be solved;

[0091] The fault recovery model to be solved is then solved to obtain the optimization results;

[0092] Based on the optimization results, a fault recovery scheme for AC / DC hybrid distribution network is obtained, and the AC / DC hybrid distribution network fault recovery scheme is used to perform fault recovery on the AC / DC hybrid distribution network.

[0093] The optimization results include at least one of the following: node power-on status and line on / off status.

[0094] In this embodiment, the fault recovery model includes an objective function and its corresponding constraints, which aim to minimize the weighted load loss and network loss power of the AC / DC hybrid distribution network.

[0095] In one implementation, the objective function is as follows:

[0096] min(C LOAD +P loss )

[0097] In the above formula, C LOAD For the weighted load loss of the AC / DC hybrid distribution network, P loss This refers to the power loss of the AC / DC hybrid distribution network.

[0098] In one implementation, the weighted load loss of the AC / DC hybrid distribution network is as follows:

[0099]

[0100] The power loss of the AC / DC hybrid distribution network is as follows:

[0101]

[0102] In the above formula, Let N be the active load of the i-th node in time period t. T Let w be the total number of fault time intervals, N be the total number of nodes, and w be the total number of fault time intervals. i Let y be the weighting coefficient for the load of the i-th node. i The variable is 0-1, representing the power-on state of node i, where 0 indicates power off and 1 indicates power on. ac For the collection of AC lines, L dc For a collection of DC lines, I l,t R is the current in branch l. l Let be the resistance of branch l.

[0103] In one implementation, the constraints include: power balance constraints, maintenance constraints, connectivity and radial constraints, and voltage and current constraints.

[0104] In one implementation, the power balance constraint is as follows:

[0105]

[0106] The maintenance constraints are as follows:

[0107]

[0108] The connectivity and radial constraints are as follows:

[0109]

[0110]

[0111] The voltage and current constraints are as follows:

[0112]

[0113] In the above formula, Ω acb For the set of AC branches, Ω dcb Let P be a set of DC lines, where l(j,:) represents a branch l starting at node j, and l(:,j) represents a branch l ending at node j. l,t Q l,t These represent the active power and reactive power of branch l during time period t, respectively, R. l and X l The resistance and reactance of branch l are respectively, and y i,t The variable is 0-1, representing the power supply status of node i during time period t, where 0 indicates power failure and 1 indicates power supply. j,t The variable is 0-1, representing the power supply status of node j during time period t, where 0 indicates power failure and 1 indicates power supply. This represents the replacement of the squared voltage variable at node j during time period t. This represents the replacement of the squared voltage variable at node i during time period t. This represents the substitution of the squared current variable in branch l during time period t. To represent the substitution of the squared active power variable at node i in time period t, To represent the substitution of the squared reactive power variable at node i during time period t. Let be the active power of the conventional generating units at node j during time period t. Let be the active power of the distributed power source at node j during time period t. Let be the energy storage discharge power of node j during time period t. Let be the energy storage charging power of node j during time period t. Let t be the active load of node j in time period t. Let t be the reactive power of the conventional generating units at node j during time period t. Y represents the reactive load of node j during time period t. ij Let t be a 0-1 variable representing the on / off state of line ij, F be the set of all faulty lines in the distribution network, and t be a variable representing the on / off state of line ij. m t n The time during the fault period, For t m The on / off state of line ij at time 1. For t nThe on / off state of line ij at time 1. For t m +T f The on / off status of line ij during the time period, T f The time required to repair one line, K is the maximum number of lines that can be repaired simultaneously within a time period, and F is the time required to repair one line. jk,t F represents the virtual power of the line between node j and node k during time period t. ij,t Let L represent the virtual power of the line between node i and node j during time period t, DG be the set of distributed power generation nodes, l(j,k) be the set of lines for line jk, and l(i,j) be the set of lines for line ij. j,t This represents the power provided by the source node in the virtual network during time period t, where M is a constant and N is a variable. DG Indicates the number of distributed power sources. and These are the squares of the upper and lower limits of the node voltage, respectively. Y is the square of the maximum allowable current of the branch. ij,t The on / off status of line ij during time period t.

[0114] In one embodiment, the step of performing fuzzy chance constraint relaxation and second-order cone relaxation on the fault recovery model corresponding to the AC / DC hybrid distribution network to obtain the fault recovery model to be solved includes:

[0115] Regarding the and Perform fuzzy chance constraint relaxation to obtain fuzzy chance relaxation constraints, and then use the fuzzy chance relaxation constraints to apply the following to the... and Replace;

[0116] Regarding the and Perform second-order cone relaxation to obtain second-order cone relaxation constraints, and use the second-order cone relaxation constraints to apply to the... and Replace it.

[0117] In one implementation, the fuzzy chance relaxation constraint is as follows:

[0118]

[0119] The second-order cone relaxation constraint is as follows:

[0120]

[0121] In the above formula, α is the confidence level, and P WT,t,1 P WT,t,2 P represents the first and second membership parameters of the fan. PV,t,1 PPV,t,2 These are the first and second membership parameters for photovoltaics.

[0122] In one specific implementation, the embodiment focuses on an improved IEEE 33-node power distribution system, whose fault diagram is shown below. Figure 2 As shown in the figure, 8 dc Node 8 represents DC node, and the rest are similarly represented. Nodes without the "dc" designation represent AC nodes, and those with "dc" designation represent DC nodes. ESS represents energy storage, VSC represents voltage source converter, WT represents wind turbine, PV represents photovoltaic generator, and L represents line. The distribution of load levels and weighting coefficients for each node is shown in Table 1.

[0123] Table 1

[0124]

[0125]

[0126] The load level and controllability of each node are set. First-level loads are set as uncontrollable loads, while second-level and third-level loads are treated as controllable loads.

[0127] The recovery results of a multi-line fault in an AC / DC hybrid distribution network during the period from 9:00 AM to 12:00 PM are shown in Table 2. Figure 3 , Figure 4 , Figure 5 , Figure 6 The topology restoration results are shown for each of the four time periods.

[0128] Table 2

[0129]

[0130] When a fault occurs in an AC / DC hybrid distribution network, the change in node voltage amplitude is an important indicator for assessing the network's operational status and recovery effectiveness. Figure 7 The voltage amplitude distribution of each node is shown in four time periods. For ease of description, DC nodes 1-10 are represented by nodes 38-47.

[0131] The fault recovery results are shown in Table 3 when the confidence level α of the fuzzy chance constraint takes different values. As the confidence level α increases, the load recovery ratio of the AC / DC hybrid distribution network gradually decreases, and the fault recovery cost continuously increases.

[0132] Table 3

[0133]

[0134] Example 2

[0135] Based on the same inventive concept, the present invention also provides an AC / DC hybrid distribution network fault recovery device, the AC / DC hybrid distribution network fault recovery device comprising:

[0136] The conversion module is used to perform fuzzy chance constraint relaxation and second-order cone relaxation on the fault recovery model corresponding to the AC / DC hybrid distribution network to obtain the fault recovery model to be solved.

[0137] The analysis module is used to solve the fault recovery model to be solved and obtain the optimization results;

[0138] The recovery module is used to obtain a fault recovery scheme for the AC / DC hybrid distribution network based on the optimization results, and to perform fault recovery on the AC / DC hybrid distribution network using the AC / DC hybrid distribution network fault recovery scheme;

[0139] The optimization results include at least one of the following: node power-on status and line on / off status.

[0140] Preferably, the fault recovery model includes: an objective function and its corresponding constraints aimed at minimizing the weighted load loss and network power loss of the AC / DC hybrid distribution network.

[0141] Furthermore, the objective function is as follows:

[0142] min(C LOAD +P loss )

[0143] In the above formula, C LOAD For the weighted load loss of the AC / DC hybrid distribution network, P loss This refers to the power loss of the AC / DC hybrid distribution network.

[0144] Furthermore, the weighted load loss of the AC / DC hybrid distribution network is as follows:

[0145]

[0146] The power loss of the AC / DC hybrid distribution network is as follows:

[0147]

[0148] In the above formula, Let N be the active load of the i-th node in time period t. T Let w be the total number of fault time intervals, N be the total number of nodes, and w be the total number of fault time intervals. i Let y be the weighting coefficient for the load of the i-th node. i The variable is 0-1, representing the power-on state of node i, where 0 indicates power off and 1 indicates power on. ac For the collection of AC lines, L dc For a collection of DC lines, Il,t R is the current in branch l. l Let be the resistance of branch l.

[0149] Furthermore, the constraints include: power balance constraints, maintenance constraints, connectivity and radial constraints, and voltage and current constraints.

[0150] Furthermore, the power balance constraint is as follows:

[0151]

[0152]

[0153] The maintenance constraints are as follows:

[0154]

[0155] The connectivity and radial constraints are as follows:

[0156]

[0157] The voltage and current constraints are as follows:

[0158]

[0159] In the above formula, Ω acb For the set of AC branches, Ω dcb Let P be a set of DC lines, where l(j,:) represents a branch l starting at node j, and l(:,j) represents a branch l ending at node j. l,t Q l,t These represent the active power and reactive power of branch l during time period t, respectively, R. l and X l The resistance and reactance of branch l are respectively, and y i,t The variable is 0-1, representing the power supply status of node i during time period t, where 0 indicates power failure and 1 indicates power supply. j,t The variable is 0-1, representing the power supply status of node j during time period t, where 0 indicates power failure and 1 indicates power supply. This represents the replacement of the squared voltage variable at node j during time period t. This represents the replacement of the squared voltage variable at node i during time period t. This represents the substitution of the squared current variable in branch l during time period t. To represent the substitution of the squared active power variable at node i in time period t, To represent the substitution of the squared reactive power variable at node i during time period t. Let be the active power of the conventional generating units at node j during time period t. Let be the active power of the distributed power source at node j during time period t. Let be the energy storage discharge power of node j during time period t. Let be the energy storage charging power of node j during time period t. Let t be the active load of node j in time period t. Let t be the reactive power of the conventional generating units at node j during time period t. Y represents the reactive load of node j during time period t. ij Let t be a 0-1 variable representing the on / off state of line ij, F be the set of all faulty lines in the distribution network, and t be a variable representing the on / off state of line ij. m t n The time during the fault period, For t m The on / off state of line ij at time 1. For t n The on / off state of line ij at time 1. For t m +T f The on / off status of line ij during the time period, T f The time required to repair one line, K is the maximum number of lines that can be repaired simultaneously within a time period, and F is the time required to repair one line. jk,t F represents the virtual power of the line between node j and node k during time period t. ij,t Let L represent the virtual power of the line between node i and node j during time period t, DG be the set of distributed power generation nodes, l(j,k) be the set of lines for line jk, and l(i,j) be the set of lines for line ij. j,t This represents the power provided by the source node in the virtual network during time period t, where M is a constant and N is a variable. DG Indicates the number of distributed power sources. and These are the squares of the upper and lower limits of the node voltage, respectively. Y is the square of the maximum allowable current of the branch. ij,t The on / off status of line ij during time period t.

[0160] Furthermore, the conversion module is specifically used for:

[0161] Regarding the and Perform fuzzy chance constraint relaxation to obtain fuzzy chance relaxation constraints, and then use the fuzzy chance relaxation constraints to apply the following to the... and Replace;

[0162] Regarding the and Perform second-order cone relaxation to obtain second-order cone relaxation constraints, and use the second-order cone relaxation constraints to apply to the... and Replace it.

[0163] Furthermore, the fuzzy chance relaxation constraint is as follows:

[0164]

[0165] The second-order cone relaxation constraint is as follows:

[0166]

[0167]

[0168] In the above formula, α is the confidence level, and P WT,t,1 P WT,t,2 P represents the first and second membership parameters of the fan. PV,t,1 P PV,t,2 These are the first and second membership parameters for photovoltaics.

[0169] Example 3

[0170] Based on the same inventive concept, this invention also provides a computer device, which includes a processor and a memory. The memory stores a computer program, which includes program instructions. The processor executes the program instructions stored in the computer storage medium. The processor may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing and control core of the terminal, suitable for implementing one or more instructions, specifically suitable for loading and executing one or more instructions in the computer storage medium to implement corresponding method flows or corresponding functions, thereby realizing the steps of the AC / DC hybrid distribution network fault recovery method in the above embodiments.

[0171] Example 4

[0172] Based on the same inventive concept, this invention also provides a storage medium, specifically a computer-readable storage medium (Memory), which is a memory device in a computer device used to store programs and data. It is understood that the computer-readable storage medium here can include both the built-in storage medium in the computer device and extended storage media supported by the computer device. The computer-readable storage medium provides storage space that stores the terminal's operating system. Furthermore, this storage space also stores one or more instructions suitable for loading and execution by a processor. These instructions can be one or more computer programs (including program code). It should be noted that the computer-readable storage medium here can be a high-speed RAM memory or a non-volatile memory, such as at least one disk storage device. The processor can load and execute one or more instructions stored in the computer-readable storage medium to implement the steps of the AC / DC hybrid power distribution network fault recovery method in the above embodiments.

[0173] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0174] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0175] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0176] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0177] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do 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 fault recovery method for an AC / DC hybrid distribution network, characterized in that, The method includes: Fuzzy chance constraint relaxation and second-order cone relaxation are applied to the fault recovery model corresponding to the AC / DC hybrid distribution network to obtain the fault recovery model to be solved. The fault recovery model to be solved is then solved to obtain the optimization results; Based on the optimization results, a fault recovery scheme for AC / DC hybrid distribution network is obtained, and the AC / DC hybrid distribution network fault recovery scheme is used to perform fault recovery on the AC / DC hybrid distribution network. The optimization results include at least one of the following: node power-on status and line on / off status.

2. The method as described in claim 1, characterized in that, The fault recovery model includes an objective function and its corresponding constraints, which aim to minimize the weighted load loss and network power loss of the AC / DC hybrid distribution network.

3. The method as described in claim 2, characterized in that, The objective function is as follows: min(C LOAD +P loss ) In the above formula, C LOAD For the weighted load loss of the AC / DC hybrid distribution network, P loss This refers to the power loss of the AC / DC hybrid distribution network.

4. The method as described in claim 3, characterized in that, The weighted load loss of the AC / DC hybrid distribution network is as follows: The power loss of the AC / DC hybrid distribution network is as follows: In the above formula, Let N be the active load of the i-th node in time period t. T Let w be the total number of fault time intervals, N be the total number of nodes, and w be the total number of fault time intervals. i Let y be the weighting coefficient for the load of the i-th node. i The variable is 0-1, representing the power-on state of node i, where 0 indicates power off and 1 indicates power on. ac For the collection of AC lines, L dc For a collection of DC lines, I l,t R is the current in branch l. l Let be the resistance of branch l.

5. The method as described in claim 4, characterized in that, The constraints include: power balance constraints, maintenance constraints, connectivity and radial constraints, and voltage and current constraints.

6. The method as described in claim 5, characterized in that, The power balance constraints are as follows: The maintenance constraints are as follows: The connectivity and radial constraints are as follows: -MY ij,t ≤F ij,t ≤MY ij,t W j,t ≥1,j∈{DG} ∑Y ij =N-N DG The voltage and current constraints are as follows: In the above formula, Ω acb For the set of AC branches, Ω dcb Let P be a set of DC lines, where l(j,:) represents a branch l starting at node j, and l(:,j) represents a branch l ending at node j. l,t Q l,t These represent the active power and reactive power of branch l during time period t, respectively, R. l and X l The resistance and reactance of branch l are respectively, and y i,t The variable is 0-1, representing the power supply status of node i during time period t, where 0 indicates power failure and 1 indicates power supply. j,t The variable is 0-1, representing the power supply status of node j during time period t, where 0 indicates power failure and 1 indicates power supply. This represents the replacement of the squared voltage variable at node j during time period t. This represents the replacement of the squared voltage variable at node i during time period t. This represents the substitution of the squared current variable in branch l during time period t. To represent the substitution of the squared active power variable at node i in time period t, To represent the substitution of the squared reactive power variable at node i during time period t. Let be the active power of the conventional generating units at node j during time period t. Let be the active power of the distributed power source at node j during time period t. Let be the energy storage discharge power at node j during time period t. Let be the energy storage charging power of node j during time period t. Let t be the active load of node j in time period t. Let t be the reactive power of the conventional generating units at node j during time period t. Y represents the reactive load of node j during time period t. ij Let t be a 0-1 variable representing the on / off state of line ij, F be the set of all faulty lines in the distribution network, and t be a variable representing the on / off state of line ij. m t n The time during the fault period, For t m The on / off state of line ij at time 1. For t n The on / off state of line ij at time 1. For t m +T f The on / off status of line ij during the time period, T f The time required to repair one line, K is the maximum number of lines that can be repaired simultaneously within a time period, and F is the time required to repair one line. jk,t F represents the virtual power of the line between node j and node k during time period t. ij,t Let L represent the virtual power of the line between node i and node j during time period t, DG be the set of distributed power generation nodes, l(j,k) be the set of lines for line jk, and l(i,j) be the set of lines for line ij. j,t This represents the power provided by the source node in the virtual network during time period t, where M is a constant and N is a variable. DG Indicates the number of distributed power sources. and These are the squares of the upper and lower limits of the node voltage, respectively. Y is the square of the maximum allowable current of the branch. ij,t The on / off status of line ij during time period t.

7. The method as described in claim 6, characterized in that, The fault recovery model corresponding to the AC / DC hybrid distribution network is subjected to fuzzy chance constraint relaxation and second-order cone relaxation to obtain the fault recovery model to be solved, including: Regarding the and Perform fuzzy chance constraint relaxation to obtain fuzzy chance relaxation constraints, and then use the fuzzy chance relaxation constraints to apply the following to the... and Replace; Regarding the and Perform second-order cone relaxation to obtain second-order cone relaxation constraints, and use the second-order cone relaxation constraints to apply to the... and Replace it.

8. The method as described in claim 7, characterized in that, The fuzzy chance relaxation constraint is as follows: The second-order cone relaxation constraint is as follows: In the above formula, α is the confidence level, and P WT,t,1 P WT,t,2 P represents the first and second membership parameters of the fan. PV,t,1 P PV,t,2 These are the first and second membership parameters for photovoltaics.

9. A fault recovery device for an AC / DC hybrid distribution network, characterized in that, The device includes: The conversion module is used to perform fuzzy chance constraint relaxation and second-order cone relaxation on the fault recovery model corresponding to the AC / DC hybrid distribution network to obtain the fault recovery model to be solved. The analysis module is used to solve the fault recovery model to be solved and obtain the optimization results; The recovery module is used to obtain a fault recovery scheme for the AC / DC hybrid distribution network based on the optimization results, and to perform fault recovery on the AC / DC hybrid distribution network using the AC / DC hybrid distribution network fault recovery scheme; The optimization results include at least one of the following: node power-on status and line on / off status.

10. The apparatus as claimed in claim 9, characterized in that, The fault recovery model includes an objective function and its corresponding constraints, which aim to minimize the weighted load loss and network power loss of the AC / DC hybrid distribution network.

11. The apparatus as claimed in claim 10, characterized in that, The objective function is as follows: min(C LOAD +P loss ) In the above formula, C LOAD For the weighted load loss of the AC / DC hybrid distribution network, P loss This refers to the power loss of the AC / DC hybrid distribution network.

12. The apparatus as claimed in claim 11, characterized in that, The weighted load loss of the AC / DC hybrid distribution network is as follows: The power loss of the AC / DC hybrid distribution network is as follows: In the above formula, Let N be the active load of the i-th node in time period t. T Let w be the total number of fault time intervals, N be the total number of nodes, and w be the total number of fault time intervals. i Let y be the weighting coefficient for the load of the i-th node. i The variable is 0-1, representing the power-on state of node i, where 0 indicates power off and 1 indicates power on. ac For the collection of AC lines, L dc For a collection of DC lines, I l,t R is the current in branch l. l Let be the resistance of branch l.

13. The apparatus as claimed in claim 12, characterized in that, The constraints include: power balance constraints, maintenance constraints, connectivity and radial constraints, and voltage and current constraints.

14. The apparatus as claimed in claim 13, characterized in that, The power balance constraints are as follows: The maintenance constraints are as follows: The connectivity and radial constraints are as follows: -MY ij,t ≤F ij,t ≤MY ij,t W j,t ≥1,j∈{DG} ∑Y ij =N-N DG The voltage and current constraints are as follows: In the above formula, Ω acb For the set of AC branches, Ω dcb Let P be a set of DC lines, where l(j,:) represents a branch l starting at node j, and l(:,j) represents a branch l ending at node j. l,t Q l,t These represent the active power and reactive power of branch l during time period t, respectively, R. l and X l The resistance and reactance of branch l are respectively, and y i,t The variable is 0-1, representing the power supply status of node i during time period t, where 0 indicates power failure and 1 indicates power supply. j,t The variable is 0-1, representing the power supply status of node j during time period t, where 0 indicates power failure and 1 indicates power supply. This represents the replacement of the squared voltage variable at node j during time period t. This represents the replacement of the squared voltage variable at node i during time period t. This represents the substitution of the squared current variable in branch l during time period t. To represent the substitution of the squared active power variable at node i in time period t, To represent the substitution of the squared reactive power variable at node i during time period t. Let be the active power of the conventional generating units at node j during time period t. Let be the active power of the distributed power source at node j during time period t. Let be the energy storage discharge power of node j during time period t. Let be the energy storage charging power of node j during time period t. Let t be the active load of node j in time period t. Let t be the reactive power of the conventional generating units at node j during time period t. Y represents the reactive load of node j during time period t. ij Let t be a 0-1 variable representing the on / off state of line ij, F be the set of all faulty lines in the distribution network, and t be a variable representing the on / off state of line ij. m t n The time during the fault period, For t m The on / off state of line ij at time 1. For t n The on / off state of line ij at time 1. For t m +T f The on / off status of line ij during the time period, T f The time required to repair one line, K is the maximum number of lines that can be repaired simultaneously within a time period, and F is the time required to repair one line. jk,t F represents the virtual power of the line between node j and node k during time period t. ij,t Let L represent the virtual power of the line between node i and node j during time period t, DG be the set of distributed power generation nodes, l(j,k) be the set of lines for line jk, and l(i,j) be the set of lines for line ij. j,t This represents the power provided by the source node in the virtual network during time period t, where M is a constant and N is a variable. DG Indicates the number of distributed power sources. and These are the squares of the upper and lower limits of the node voltage, respectively. Y is the square of the maximum allowable current of the branch. ij,t The on / off status of line ij during time period t.

15. The apparatus as claimed in claim 14, characterized in that, The conversion module is specifically used for: Regarding the and Perform fuzzy chance constraint relaxation to obtain fuzzy chance relaxation constraints, and then use the fuzzy chance relaxation constraints to apply the following to the... and Replace; Regarding the and Perform second-order cone relaxation to obtain second-order cone relaxation constraints, and use the second-order cone relaxation constraints to apply to the... and Replace it.

16. The apparatus as claimed in claim 15, characterized in that, The fuzzy chance relaxation constraint is as follows: The second-order cone relaxation constraint is as follows: In the above formula, α is the confidence level, and P WT,t,1 P WT,t,2 P represents the first and second membership parameters of the fan. PV,t,1 P PV,t,2 These are the first and second membership parameters for photovoltaics.

17. A computer device, characterized in that, include: One or more processors; The processor is used to execute one or more programs; When the one or more programs are executed by the one or more processors, the AC / DC hybrid distribution network fault recovery method as described in any one of claims 1 to 8 is implemented.

18. A computer-readable storage medium, characterized in that, It contains a computer program, which, when executed, implements the AC / DC hybrid distribution network fault recovery method as described in any one of claims 1 to 8.

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