A method for fault recovery and reliability assessment of flexible interconnected distribution networks

Abstract

The present invention relates to a method for fault recovery and reliability assessment of a flexible interconnected distribution network, comprising the following steps: obtaining basic parameters and reliability parameters of a distribution network, constructing a node-branch state association relationship of a flexible interconnected distribution network; considering the intelligent soft switch recovery power constraint and short-term overload capacity, establishing an intelligent soft switch rapid recovery model of a flexible interconnected distribution network; based on the flexible interconnected distribution network node-branch state association relationship and the intelligent soft switch rapid recovery model, considering a multi-stage recovery process, constructing constraint conditions, and establishing a mixed integer linear programming model for fault recovery and reliability assessment of a flexible interconnected distribution network, the mixed integer linear programming model takes the minimum average power outage time of the system as the objective function; solving the mixed integer linear programming model, and obtaining a flexible interconnected distribution network fault recovery strategy and reliability assessment results. Compared with the prior art, the present invention has the advantages of reducing load power outage losses and a high level of refinement.

Description

Technical Field

[0001] The present invention belongs to the technical field of distribution network fault recovery and reliability assessment, and in particular to a flexible interconnected distribution network fault recovery and reliability assessment method. Background Art

[0002] With the rapid development of smart grids, the safety and reliability of the distribution network, as a key link in the power system directly connected to users, are increasingly valued. As an upgraded form of the traditional distribution network, the flexible interconnected distribution network has achieved flexible adjustment of the grid structure and rapid recovery of faults by introducing advanced power electronic equipment and intelligent control technology, significantly improving the power supply reliability and self-healing ability of the system. As a new type of distribution component that replaces the traditional tie switch, the intelligent soft switch (soft open point, SOP) can realize the flexible closed-loop operation of the distribution network, balance the load, promote the consumption of new energy, and improve the utilization rate of equipment. Therefore, it has gradually been applied to practical projects.

[0003] Fault recovery processing is an important part of the operation and maintenance management of flexible interconnected distribution networks. It aims to quickly identify the fault location, isolate the fault area, and restore power supply to non-fault areas by optimizing the dispatching strategy. At the same time, reliability is one of the core goals of distribution network planning and construction, and reliability assessment is crucial to the planning and construction of flexible interconnected distribution networks. How to make the fault recovery and reliability assessment of flexible interconnected distribution networks adapt to the needs of high-quality development of distribution networks under the new situation, reduce load power outage losses, and improve the refinement level of reliability assessment is a technical problem that needs to be solved urgently in this field. Summary of the invention

[0004] The purpose of the present invention is to overcome the defects of the above-mentioned prior art and provide a flexible interconnected distribution network fault recovery and reliability assessment method to achieve rapid recovery of flexible interconnected distribution network faults, reduce load power outage losses, improve the level of reliability assessment refinement, and guide the flexible planning and construction of distribution networks. It is suitable for fault recovery and reliability assessment scenarios of 110kV and below flexible interconnected distribution networks.

[0005] The purpose of the present invention can be achieved by the following technical solutions:

[0006] A method for fault recovery and reliability assessment of a flexible interconnected distribution network comprises the following steps:

[0007] Obtain basic distribution network parameters such as topology, line parameters, equipment parameters, source / load scenarios, etc.; obtain distribution network reliability parameters such as fault scenario set, component failure rate, fault location isolation time, and action time of each recovery stage; establish an intelligent soft switch equivalent model for fault recovery and reliability evaluation; and construct a node-branch status association relationship of a flexible interconnected distribution network;

[0008] Considering the power recovery constraint and short-term overload capacity of the intelligent soft switch, a fast recovery model of the intelligent soft switch for flexible interconnected distribution network is established.

[0009] Based on the node-branch state association relationship of the flexible interconnected distribution network and the intelligent soft switch fast recovery model, a multi-stage recovery process is considered, constraints are constructed, and a mixed integer linear programming model for fault recovery and reliability evaluation of the flexible interconnected distribution network is established. The mixed integer linear programming model takes the minimum average power outage time of the system as the objective function;

[0010] The mixed integer linear programming model is solved to obtain the fault recovery strategy and reliability evaluation results of the flexible interconnected distribution network.

[0011] Furthermore, the intelligent soft switch equivalent model is expressed as:

[0012]

[0013] The node-branch state association relationship of the flexible interconnected distribution network is expressed as:

[0014]

[0015] Where: is a 0-1 variable or parameter, indicating the state of node i. If it is in a power outage state, otherwise It is a 0-1 variable or parameter, indicating the state of branch ij. If it is in a power-off state, otherwise is a 0-1 variable or parameter, indicating the switch status of the branch ij node i or j. If it is in the open state, otherwise The subscripts ω and τ represent the source / load scenario and different stages, respectively. Ψ Sc and T Respectively represent the source / load scenario set and the stage set, and Ψ T ={τ FB ,τ LI ,τ FT ,τ UR ,τ TT ,τ IO}, τ FB , τ LI , τ FT , τ UR , τ TT , τ IOThey represent fault blocking, fault location isolation, intelligent soft switch fast recovery, fault point upstream recovery, tie switch switching recovery and island operation recovery stages respectively; the superscript μν represents the fault scenario, F.F SOP and F S ' OP They represent the fault scenario set, intelligent soft switch fault scenario set, and intelligent soft switch function fault scenario set respectively; the superscript κ is the switch type, K is the switch set, κ N , κ SOP , κ CB , κ LS Respectively represent no switch, intelligent soft switch equivalent switch, circuit breaker and load switch. Β SOP is the intelligent soft switch branch set; Β is the branch set.

[0016] Furthermore, the intelligent soft switch rapid recovery model is constructed based on the intelligent soft switch recovery power constraint and the intelligent soft switch short-time overload capacity constraint. The intelligent soft switch short-time overload capacity constraint is characterized by the power outage load recovery situation determined by combining the maximum overload operation time and overload elimination time of the intelligent soft switch when the load to be restored is greater than the capacity of the intelligent soft switch itself.

[0017] Furthermore, the intelligent soft switch recovery power constraint is expressed as:

[0018]

[0019] Where: are the active and reactive powers of the intelligent soft-switching converter at node m or n respectively; is the intelligent soft switch capacity on branch mn; is a 0-1 variable or parameter, indicating the state of node m or n. If it is in a power-off state, otherwise It is a 0-1 variable or parameter, indicating the state of branch mn. If it is in a power-off state, otherwise The superscript μν indicates the fault scenario, Β SOP is the set of intelligent soft switch branches; the subscript τ represents different stages, Ψ T represents the set of stages, τ FB Indicates the fault blocking stage.

[0020] Furthermore, the short-time overload capacity constraint of the intelligent soft switch is expressed as:

[0021]

[0022] Where: The operating time at maximum overload and overload elimination time After logical judgment, the power outage time of load point i under fault rapid recovery; express Load outage time under certain conditions; express Load power outage time under the condition; F SOP N represents the intelligent soft switch fault scenario set; LP is a set of load points.

[0023] Furthermore, the Load outage time under the condition It is expressed as:

[0024]

[0025] Where: is the state of load point i when the intelligent soft switch is not considered to restore the power constraint; and They are respectively the fault location isolation time and the fault repair time, τ FT Indicates the intelligent soft switch fast recovery stage.

[0026] Furthermore, the Load outage time under the condition It is expressed as:

[0027]

[0028] Where: is the state of load point i when the intelligent soft switch is not considered to restore the power constraint; and They are respectively the fault location isolation time and the fault repair time, τ FB , τ FT They represent the fault blocking stage and the intelligent soft switch fast recovery stage respectively.

[0029] Furthermore, the constructed constraints include fault scenario setting constraints, node-branch state association constraints, fault blocking constraints, fault isolation constraints, fault recovery constraints, load point reliability calculation constraints and system reliability calculation constraints.

[0030] Furthermore, the fault recovery constraints specifically include switch constraints at different recovery stages, intelligent soft switch operation constraints at different recovery stages, distributed power supply operation constraints at different recovery stages, flexible interconnected distribution network operation constraints at different recovery stages and actual power outage time constraints.

[0031] Furthermore, the reliability assessment result includes the value of the reliability assessment index of the flexible interconnected distribution network, and the reliability assessment index of the flexible interconnected distribution network includes the system average power outage frequency, the system average power outage time, the system average power supply reliability rate and the system power shortage amount.

[0032] Compared with the prior art, the present invention has the following beneficial effects:

[0033] (1) The present invention considers the power recovery constraint and short-term overload capacity of the intelligent soft switch, establishes an intelligent soft switch rapid recovery model for the flexible interconnected distribution network, gives full play to the fault recovery function of the intelligent soft switch, realizes rapid recovery of faults in the flexible interconnected distribution network, and reduces load power outage losses.

[0034] (2) The present invention takes into account the multi-stage recovery process after a fault in the reliability assessment of the flexible interconnected distribution network, including rapid recovery of the intelligent soft switch, upstream recovery of the fault point, recovery of the interconnecting switch switching, and recovery of the island operation, which effectively improves the refinement level of the reliability assessment and the accuracy of the assessment results. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 is a flow chart of the method of the present invention;

[0036] Figure 2 Schematic diagram of the equivalent model of intelligent soft switch for fault recovery and reliability evaluation;

[0037] Figure 3 It is the inverse time characteristic diagram of the short-time overload capacity of the intelligent soft switch;

[0038] Figure 4 Calculation flow chart for system reliability index;

[0039] Figure 5 The diagram is for the improved 37-node reliability test system;

[0040] Figure 6 is the peak load diagram of each node;

[0041] Figure 7 The diagram shows the fast recovery of intelligent soft switch under three strategies;

[0042] Figure 8 The reliability change diagram of the flexible interconnected distribution network under different intelligent soft switch capacities;

[0043] Fig. 9 This is a multi-stage restoration process diagram for the flexible interconnected distribution network;

[0044] Fig.10 This is a diagram of the single-stage restoration process of the flexible interconnected distribution network. DETAILED DESCRIPTION

[0045] The present invention is described in detail below in conjunction with the accompanying drawings and specific embodiments. This embodiment is implemented based on the technical solution of the present invention, and provides a detailed implementation method and specific operation process, but the protection scope of the present invention is not limited to the following embodiments.

[0046] This embodiment provides a method for fault recovery and reliability assessment of a flexible interconnected distribution network. Figure 1 As shown, the following steps are included:

[0047] S1. Obtain basic distribution network parameters such as topology, line parameters, equipment parameters, source / load scenarios, etc.; obtain distribution network reliability parameters such as fault scenario set, component failure rate, fault location isolation time, and action time of each recovery stage; establish an intelligent soft switch equivalent model for fault recovery and reliability evaluation; and construct a node-branch status association relationship for a flexible interconnected distribution network;

[0048] S2. Considering the power constraint and short-term overload capacity of intelligent soft switch recovery, a fast recovery model of intelligent soft switch for flexible interconnected distribution network is established;

[0049] S3. Based on the node-branch state association relationship of the flexible interconnected distribution network and the intelligent soft switch fast recovery model, a multi-stage recovery process is considered, constraints are constructed, and a mixed integer linear programming model for fault recovery and reliability evaluation of the flexible interconnected distribution network is established. The mixed integer linear programming model aims to minimize the average power outage time of the system;

[0050] S4. Solve the mixed integer linear programming model to obtain the fault recovery strategy and reliability evaluation results of the flexible interconnected distribution network.

[0051] The above method fully considers the short-term overload capacity of the intelligent soft switch in the fault recovery process, and comprehensively considers multiple stages such as intelligent soft switch rapid recovery, upstream recovery of the fault point, interconnection switch switching recovery, and island operation recovery in the fault recovery constraints. It also combines fault scenario setting, node-branch status association, fault blocking, fault isolation, load point reliability calculation and other constraints, and constructs a mixed integer linear programming model for fault recovery and reliability assessment of flexible interconnected distribution networks with the goal of minimizing the average power outage time of the system.

[0052] The specific technical features of the above method are described as follows.

[0053] 1. Reliability evaluation indicators of flexible interconnected distribution network

[0054] The reliability evaluation indicators of flexible interconnected distribution network mainly include: system average power outage frequency (I SAIFI ), system average power outage time (I SAIDI ), system average power supply reliability rate (I ASAI) and system power shortage (I ENS ), as shown in equations (1) to (4).

[0055]

[0056] I ASAI =(1-I SAIDI / 8760)×100% (3)

[0057]

[0058] Where: LP,i , U LP,i and E LP,i are the outage rate, outage time and expected value of power shortage at load point i respectively; LP is the set of load points; N C,i is the number of users at load point i.

[0059] 2. Node-branch state association model

[0060] 1) When SOP is operating normally, it can achieve fault blocking and fault isolation, so:

[0061]

[0062] Where: SOP SOP branch collection

[0063] In addition, the load can be quickly restored during normal operation of the SOP.

[0064] 2) When the SOP insulation fails, it can be compared to a branch short circuit failure, with:

[0065]

[0066] 3) When the SOP function fails, it can be approximated as an open circuit failure. In this case, since no short-circuit current is generated, it is usually only necessary to isolate the fault before maintenance to avoid safety accidents. Therefore:

[0067]

[0068] Constraints (5) to (7) are the switch characteristics of the SOP under normal operation and different faults. The former in each SOP equivalent model constraint reflects whether the SOP is faulty, and the latter represents the opening and closing state of the SOP equivalent switch.

[0069] Based on the SOP equivalent model, the state association relationship between the node i(j) and the branch ij of the flexible interconnected distribution network can be further constructed, that is:

[0070]

[0071] Where: Β is the branch set, Β=Β L ∪Β TL ∪Β SOP ; Β L and Β TL They are respectively the collection of normally closed and normally open (contact) branches. Among them:

[0072] 1) When there is no switch or the switch is closed on the node i(j) side of the branch ij hour:

[0073]

[0074] That is, the state of branch ij and node i(j) is the same.

[0075] 2) When the switch on the node i(j) side of the branch ij is in the open state hour:

[0076]

[0077] That is, the states of branch ij and node i(j) do not affect each other.

[0078] Where: —0-1 variable or parameter, the state of node i, if it is in a power outage state otherwise —0-1 variable or parameter, the state of branch ij, if it is in power-off state otherwise —0-1 variable or parameter, which is the switch status of the branch ij node i or j side. If it is in the open state, otherwise The subscripts ω and τ represent the source / load scenario and different stages, respectively. Ψ Sc and T Respectively represent the source / load scenario set and the stage set, and Ψ T ={τ FB ,τ LI ,τ FT ,τ UR ,τ TT ,τ IO}, τ FB , τ LI , τ FT , τ UR , τ TT , τ IO They represent fault blocking, fault location isolation, intelligent soft switch fast recovery, fault point upstream recovery, tie switch switching recovery and island operation recovery stages respectively; the superscript μν represents the fault scenario, i.e., branch μν fault, F.F SOP and F S ' OP They represent the fault scenario set, intelligent soft switch fault scenario set, and intelligent soft switch function fault scenario set respectively; the superscript κ is the switch type. K is the switch set, κ N , κ SOP , κ CB , κ LS Respectively represent no switch, intelligent soft switch equivalent switch, circuit breaker and load switch. SOP is the intelligent soft switch branch set; Β is the branch set.

[0079] 3. Intelligent soft switch fast recovery model

[0080] Due to its own capacity limitation, the intelligent soft switch may not be able to fully restore the load. Therefore, based on the node-branch state association model, the intelligent soft switch recovery power constraint and short-term overload capacity are considered to further establish a rapid recovery model of the intelligent soft switch.

[0081] 3.1 Intelligent soft switching to restore power constraints

[0082] Combining the virtual node state and the SOP equivalent branch state, the SOP recovery power constraint can be established, namely:

[0083]

[0084]

[0085] Where: are the active and reactive powers of the SOP converter at node m or n, respectively; is the SOP capacity on branch mn. Equations (11) to (12) reflect the impact of external faults and internal faults on the SOP output power. The virtual node m(n) is the state flag node for the SOP injection power. Figure 2 As shown in Figure 1, when the virtual node m(n) is in a power outage state due to external fault association or the SOP itself fails, the SOP injection power is 0, otherwise the SOP injection power is constrained by its own capacity. In addition, the SOP's own fault condition is determined in the fault scenario setting and reflected by the SOP branch state parameter; combined with equations (5) to (7), when the SOP is operating normally, the SOP branch state is 1; when the SOP fails, the SOP branch state is 0. Equations (13) to (14) are SOP power balance and self-capacity constraints.

[0086] In addition, SOP usually considers a certain overload capacity in the design stage to adapt to the short-term load fluctuations and starting current shocks that may occur in actual operation. In addition, in conjunction with the SOP emergency control strategy in the operation stage, the SOP short-term overload capacity cannot be ignored. Therefore, in the reliability assessment of the flexible interconnected distribution network, the SOP short-term overload capacity is also worthy of attention. In this embodiment, SOP rapid recovery models under different strategies are established from the perspective of whether the SOP short-term overload capacity is considered.

[0087] 3.2 Not considering SOP short-term overload capacity

[0088] When the short-term overload capacity of SOP is not considered, it is recorded as strategy S1. If the restored load is greater than the SOP capacity, part of the load must be removed first, and then restored after the SOP recovery power constraint is met. Since the load shedding time is required, the SOP is not restored quickly at this time; on the contrary, if the restored load is less than or equal to the SOP capacity, the SOP is restored quickly. The load outage time under this strategy is:

[0089]

[0090] Where: Eliminate time for SOP overload; and They are fault location isolation time and fault repair time respectively; is an auxiliary 0-1 variable reflecting the state of load point i under S1, which can be characterized as:

[0091]

[0092] Where: A 0-1 variable that reflects whether the SOP is overloaded. It is 1 when the SOP is overloaded, otherwise it is 0. It satisfies the following constraints:

[0093]

[0094] Where: is the apparent power of load point i; LP,μν and N LP,μν They are respectively the SOP branch set and SOP associated load point set of the feeder where the fault branch μν is located.

[0095] 3.3 Consider SOP short-term overload capacity

[0096] When considering the short-term overload capacity of SOP, if the recovery load is greater than the SOP capacity, the SOP cannot run for a long time after rapid recovery. At this time, the maximum overload operation time of SOP needs to be considered. and Determine the recovery status of the power outage load.

[0097] 1) When When The overload can be eliminated within 1 second, which is recorded as P1. At this time, the load power outage time is:

[0098]

[0099] Where: is the state of load point i when SOP recovery power constraint is not considered.

[0100] 2) When When Overload cannot be eliminated. The post-SOP is locked. At this time, the following two recovery strategies can be considered:

[0101] ① Avoid overload operation after SOP is restored by means of load shedding, etc., recorded as P2. At this time, the load power outage time is:

[0102]

[0103] ②SOP still recovers quickly, recorded as P2', to minimize the load power outage time. At this time, the load power outage time is:

[0104]

[0105] Further, eliminate and Logical judgment between P1 and P2. The recovery strategy composed of P1 and P2 is recorded as strategy S2, and we have:

[0106]

[0107] Where: is an auxiliary 0-1 variable reflecting the state of load point i under S2, which can be characterized as:

[0108]

[0109] Where: To reflect and 0-1 variable between It is 1 when , otherwise it is 0, which satisfies the following constraints:

[0110]

[0111] Where: for The maximum overload power within the SOP is:

[0112]

[0113] Where: h -1(·)for The inverse function of the maximum overload power of SOP is approximately as follows: Figure 3 As shown in the figure is the maximum overload operation time of SOP after fault isolation, S + is the ratio of SOP overload power to rated capacity, passing through points (0, M), (1.2,1), (1.5,1 / 60), (M,0) to piecewise linearize it.

[0114] The recovery strategy composed of P1 and P2' is recorded as strategy S2', then:

[0115]

[0116] The load outage time under the above different strategies is summarized as follows:

[0117]

[0118] 4. Mixed integer linear programming model for reliability assessment of flexible interconnected distribution networks

[0119] Based on the above content, a mixed integer linear programming model for reliability assessment of flexible interconnected distribution networks is further established.

[0120] 4.1 Objective Function

[0121] Based on the reliability evaluation index of the flexible interconnected distribution network, the average power outage time I SAIDI The minimum is taken as the goal and it is explicitly expressed through the node state variables to establish the objective function of the mixed integer linear programming model:

[0122]

[0123] Where: ω is the probability of source / load scenario ω; is the actual power outage time of load point i; μν is the failure rate of branch μν.

[0124] 4.2 Constraints

[0125] In addition to the constraints involved in parts 2 and 3, the mixed integer linear programming model for reliability assessment of flexible interconnected distribution networks should also meet the following constraints.

[0126] 4.2.1 Fault scenario settings

[0127] The fault scenario setting includes constraints (6) to (7) and the following constraints:

[0128]

[0129] Where: N TS is the substation node set; L is a set of normally closed distribution lines. Constraint (29) defines the state of the fault branch μν under different fault scenarios μν; constraint (30) indicates that the substation node is not affected by the fault; constraint (31) indicates the switch state when there is no switch.

[0130] 4.2.2 Fault blocking

[0131] This part of the constraints is used to describe the blocking effect of CB and SOP on faults.

[0132]

[0133] Where: is the switch state when the distribution network is operating normally, which is a known parameter for the existing distribution network. Constraints (32) to (33) respectively represent the blocking effect of SOP and CB on faults; constraint (34) indicates that switches without fault blocking capability will not operate.

[0134] 4.2.3 Fault Isolation

[0135] This part of the constraints is used to describe the isolation effect of the switch on the fault. In the case of branch insulation fault, fault isolation will not cause the load point state to change; to avoid redundant constraints, it is embedded in the fault recovery stage. In the case of SOP function failure, since there is no fault current generated, the overcurrent protection does not work. At this time, fault isolation may cause the load point state to change; to prevent unnecessary load power outages, the network should be reconstructed before fault isolation. To avoid repetition, the relevant constraints are placed in the fault recovery part later, corresponding to τ = τ LI The corresponding formula.

[0136] 4.2.4 Fault Recovery

[0137] Firstly, the coupling constraints between the multi-stage recovery processes are explained, then the decoupling basis and decoupling conditions are explained, and finally the decoupling model of the multi-stage recovery process is established.

[0138] (1) Coupling constraints between multi-stage recovery processes

[0139] The coupling constraints based on the order relationship between stages are shown in equations (35) to (38). Among them, equations (35) to (36) are the node state coupling constraints and branch state coupling constraints between stages, which indicate that the nodes or branches that have restored power supply in the previous recovery stage will still maintain the power supply state in the current recovery stage and the subsequent recovery stage; equations (37) to (38) are the switch state coupling constraints between stages, where equation (37) indicates that the switch that has been actuated in the previous recovery stage will maintain the switch state after actuation, and equation (38) indicates that the switch that has been actuated in the subsequent stage should not be actuated in advance.

[0140]

[0141] Where: τ C , τ P and τ L are the current recovery stage, the previous recovery stage, and the subsequent recovery stage; κ P and κ L They are respectively the switch for the previous recovery phase action and the switch for the subsequent recovery phase action.

[0142] (2) Decoupling basis and decoupling conditions

[0143] On the one hand, the reliability assessment modeling of distribution network aims to determine the actual power outage situation of load points (such as power outage frequency and power outage time), and then calculate the reliability index, but there is no specific requirement for the actual physical meaning of variables such as nodes, branches, and switch states in the modeling process; on the other hand, in the actual fault recovery process, no matter how many recovery methods the load point has, it is usually restored according to the method that restores power supply as early as possible. Therefore, when modeling, virtual nodes, branches, switch states and other variables that have no actual physical meaning can be introduced without affecting the final determination of the actual power outage situation of the load point (it should be noted that although these variables themselves have no actual physical meaning, they can still be inferred based on reliability parameters such as the action time of each recovery stage. Nodes, branches, and switch states with actual physical meanings) are used to eliminate the coupling relationship between the nodes, branches, and switch states of the flexible interconnected distribution network in the multi-stage recovery process to reduce the degree of dependence between different recovery stages. In simple terms, we can first establish corresponding fault recovery models for different possible recovery modes of load points (due to independent modeling, the nodes, branches and switch states of each model do not affect each other), and then determine the recovery status of each load point based on each independent model. Finally, by judging the earliest recovery mode for the load point to restore power supply, we can determine the actual power outage status of the load point. Based on the above ideas, in order to improve the adaptability of the model to different recovery sequence scenarios, the present invention will consider the multi-stage recovery of the flexible interconnected distribution network reliability assessment model for decoupling modeling. Among them, in order to ensure the accuracy of the decoupled model, the flexible interconnected distribution network for decoupling modeling should meet the following conditions:

[0144] 1) The tie line can realize the full transfer of fault downstream loads and the system meets the safety constraints after the transfer;

[0145] 2) The power supply recovery capability of SOP rapid transfer or island operation is mainly limited by the capacity of SOP or DG itself.

[0146] The above decoupling conditions require that the recovery process at each stage does not affect each other in terms of the load point recovery capacity. It should be noted that due to the functional attributes of the tie line itself, as well as the voltage support capacity of the SOP and the grid-forming DG, the above decoupling conditions are usually in line with the actual situation.

[0147] (3) Multi-stage recovery process decoupling model

[0148] Based on the above analysis, the coupling constraints (35)~(38) are decoupled to eliminate the coupling relationship between nodes, branches and switch states in different recovery stages. Switch action constraints, SOP operation constraints, DG operation constraints and flexible interconnected distribution network operation constraints that do not affect each other in different recovery stages are established. Finally, the actual recovery status of the power outage load after the multi-stage recovery process is determined by the actual power outage time constraint.

[0149] 1) Switching constraints at different recovery stages

[0150]

[0151] Equations (39) to (42) represent the switch state constraints in the SOP fast recovery, fault point upstream recovery, tie switch switching recovery, and island operation recovery stages, respectively.

[0152] 2) SOP operation constraints at different recovery stages

[0153] In addition to equations (5) and (11) to (14), the SOP operation constraints also include:

[0154]

[0155] Formula (43) indicates that whether SOP injects power during the upstream recovery of the fault point, the tie switch switching recovery and the island operation recovery stage depends on the state of the SOP virtual node in the fault blocking stage.

[0156] 3) Distributed generation DG operation constraints at different recovery stages

[0157]

[0158]

[0159] Where: and are the active power, reactive power, upper limit of active power and maximum available capacity of DG at node i respectively; and are the maximum and minimum values ​​of the DG power factor angle at node i respectively; DG is the set of DG nodes. Equations (44) to (48) constrain the output of DG at each stage.

[0160] 4) Operation constraints of flexible interconnected distribution networks at different recovery stages

[0161]

[0162] Where: and are the active and reactive powers injected at node i respectively; and are the active and reactive powers injected by the active element η at node i, respectively, η∈Λ={TS,SOP,DG}, TS is the substation; and are the active and reactive loads at node i respectively; and are the active and reactive powers flowing through branch ij respectively; is the rated transmission capacity of branch ij; r ij and x ij are the resistance and reactance of branch ij respectively; is the square of the voltage amplitude at node i; and v are the squares of the upper and lower limits of the voltage amplitude at node i, respectively; and are the active and reactive power of the substation at node i respectively; is the rated capacity of the substation at node i. Equations (49) to (53) are the power flow constraints of the flexible interconnected distribution network; Equations (54) to (55) are the operational safety constraints of the flexible interconnected distribution network; Equation (56) is the substation output constraint; and Equation (57) is the operational topology constraint of the flexible interconnected distribution network under fault conditions.

[0163] 5) Actual power outage time constraints

[0164] Before determining the actual power outage time of each load point, it is necessary to first determine the load power outage time of the recovery process at different stages under decoupling modeling, as shown in equations (58) to (59).

[0165]

[0166] Where: The power outage time of load point i under the decoupled modeling of the recovery process at each stage; {τ UR ,τ TT ,τ IO} and {UR,TT,IO} have a one-to-one correspondence, corresponding and They represent the upstream recovery time of the fault point, the tie switch switching recovery time, and the island operation recovery time respectively.

[0167] In the actual fault recovery process, for a certain load point, no matter how many recovery methods it has, the power outage time is always determined based on the method that enables it to restore power supply the earliest. Therefore, the actual power outage time of the load under the fault scenario μν is:

[0168]

[0169] 4.2.5 Load point reliability calculation

[0170]

[0171] 4.2.6 System reliability calculation

[0172] After obtaining the load point reliability index, the system reliability index can be further calculated, as shown in formulas (1) to (4). The system reliability index calculation process is as follows: Figure 4 shown.

[0173] 4.3 Model Conversion

[0174] Formulas (14), (47) to (48), (55) to (56) are all in the form The nonlinear form of (x1, y1, z1 are variables or their linear combinations) can be linearized by the inner approximation method of a regular polygon (a regular p-gon), as shown in formula (63), where p = 8.

[0175]

[0176] There are nonlinear terms of the form "x2·y2" in equations (16), (20), (22), and (57) (x2 is a 0-1 variable, y2 is a 0-1 variable or a continuous variable greater than 0). Let L2 = x2·y2 and linearize it using the Big M method:

[0177]

[0178] Formula (60) is a formula of the form “min{t i}” nonlinear form (t i is a continuous variable greater than 0, i = 1, 2, ···), let L3 = min{t i}, and linearize it by the big M method:

[0179]

[0180] Where: a i A 0-1 auxiliary variable.

[0181] The linearized form replaces the original nonlinear form, and the mixed integer linear programming model for reliability assessment of flexible interconnected distribution network is obtained. Its general form can be abstracted as:

[0182]

[0183] Where: a, b, e, h, C, D, F, G are all coefficient matrices; x is an integer variable, and y is a continuous variable. The objective function corresponds to equations (27) to (28). The fault scenario setting in the constraint conditions corresponds to equations (6) to (7), (29) to (31); NB state association corresponds to equations (8) to (10); fault blocking corresponds to equations (32) to (34); fault isolation and fault recovery correspond to equations (5), (11) to (26), (39) to (60); load point reliability calculation corresponds to equations (28), (61) to (62); system reliability calculation corresponds to equations (1) to (4).

[0184] The above model can use solvers such as GUROBI and CPLEX to obtain its global optimal solution.

[0185] 5. Case Analysis

[0186] 5.1 Test system

[0187] Improved 37-node system such as Figure 5 The system includes 1 substation node and 36 load nodes; normally open tie lines are configured between nodes 8 to 15, nodes 16 to 26, and nodes 19 to 33, respectively, to obtain a "closed-loop design, open-loop operation" distribution network; further, a grid-forming DG composed of photovoltaics and energy storage is connected at nodes 5, 22, and 30, and the traditional tie switches between nodes 8 to 15 and nodes 19 to 33 are replaced with SOPs to obtain a flexible interconnected distribution network. Among them, the distribution line failure rate is set to 0.1 times / (a·km), the insulation fault and functional fault failure rates of the intelligent soft switch are set to 0.06 times / a and 1 time / a respectively, and the intelligent soft switch capacity is set to 2MVA; the fault location isolation time of each branch, the upstream recovery time of the fault point, the contact switch switching recovery time, and the fault repair time are set to 1h, 1.3h, 1.5h and 2h respectively; since the intelligent soft switch can achieve millisecond-level rapid recovery after fault isolation, the intelligent soft switch rapid recovery time is the fault location isolation time, and the overload elimination time is set to 1.1h; the island operation recovery is used as the last means of fault recovery before fault repair, and the island operation recovery time is set to 1.6h; the peak load of each node can be seen in Figure 6 .

[0188] 5.2 Comparative analysis of reliability evaluation results

[0189] In order to verify the effectiveness of the method of the present invention, the following four scenarios are set for comparative analysis:

[0190] Scenario 1: Radial distribution network (using the method of the present invention);

[0191] Scenario 2: “Closed-loop design, open-loop operation” distribution network (single-stage network reconstruction method, post-fault network reconstruction time is set to 1.3h);

[0192] Scenario 3: “Closed-loop design, open-loop operation” distribution network (using the method of the present invention);

[0193] Scenario 4: Flexible interconnected distribution network (using the method of the present invention).

[0194] The load point reliability indicators under the four scenarios are shown in Tables 1 to 4, among which the intelligent soft switch fault fast recovery strategy model for scenario 4 adopts S1.

[0195] Table 1 Reliability index of each load point in scenario 1

[0196]

[0197] Comparing Tables 1 to 3, we can see that the U of the “closed-loop design, open-loop operation” distribution network in scenarios 2 to 3 is LP,i It is obviously lower than the radial distribution network in scenario 1; while U LP,i It is lower than scenario 3 because the single-stage network reconstruction method does not consider the multi-stage recovery process such as upstream recovery and tie switch recovery after the fault, and assumes that the recoverable loads before the fault repair are all restored within the same time of 1.3h. LP,i This is because the network topology in scenarios 1 to 3 under normal operation is the same, and the fault set elements and the failure rate of each element are also the same. It can be seen from formula (57) that the λ of scenarios 1 to 3 is LP,i It is only determined by the load node status during the fault blocking phase, and the fault recovery has no impact on it. Therefore, the λ of scenarios 1 to 3 is LP,i same.

[0198] Table 2 Reliability index of each load point in scenario 2

[0199]

[0200] Table 3 Reliability index of each load point in scenario 3

[0201]

[0202] Comparing Tables 1 to 4, we can see that the λ of scenario 4 LP,i It is significantly higher than scenarios 1 to 3. This is mainly because, unlike the radial and "closed-loop design, open-loop operation" distribution networks, the network topology of the flexible interconnected distribution network has changed under normal operation. That is, after the intelligent soft switch is connected, in addition to being a new distribution component, it also changes the traditional normally open tie line in the standby state into a normally closed operation line. The expansion of the fault set F makes the λ of the flexible interconnected distribution network LP,iAt the same time, the capacity limitation of the intelligent soft switch itself makes the load unable to be fully restored, and the direct replacement of the traditional tie switch by the intelligent soft switch causes the functional failure of the intelligent soft switch to cause the load to be out of power. Combining the above factors, U LP,i In order to reduce the power outage time caused by the expansion of fault set F, the traditional tie switch is retained on the basis of scenario 4 and scenario 5 is set to further analyze the effect of retaining the original tie switch on the reliability of the load point after the intelligent soft switch is connected.

[0203] Table 4 Reliability index of each load point in scenario 4

[0204]

[0205] Table 5 Reliability index of each load point in scenario 5

[0206]

[0207] 5.3 Comparative analysis between the method of the present invention and the traditional simulation method

[0208] In order to reflect the accuracy of the method of the present invention, it is compared with the sequential MC method. When the SOP fast transfer strategy adopts S1, the reliability evaluation results of the flexible interconnected distribution network of the two methods are shown in Table 6, where the sampling time of the sequential MC method is set to 20000a.

[0209] It can be seen from Table 6 that the calculation results of the method of the present invention are basically consistent with those of the sequential MC method, which shows the accuracy of the reliability assessment results of the flexible interconnected distribution network based on the mixed integer linear programming model of the present invention.

[0210] Table 6 Comparison of results between the method of the present invention and the traditional simulation method

[0211]

[0212] Note: Relative error = (result of the method of the present invention - result of sequential MC method) / result of sequential MC method × 100%

[0213] 5.4 Analysis of the Intelligent Soft Switch Fault Rapid Recovery Strategy Model

[0214] The reliability evaluation results of the flexible interconnected distribution network under different fault rapid recovery strategy models (S1, S2, S2') of intelligent soft switches are shown in Table 7. The rapid recovery of intelligent soft switches under the three strategies is shown in Table 7. Figure 7 As shown, the vertical axis is 1, which means the intelligent soft switch recovers quickly after the fault is isolated, otherwise it is 0.

[0215] Table 7 System reliability indicators under different recovery strategies of intelligent soft switches

[0216]

[0217] It can be seen from Table 6 that the reliability index of the flexible interconnected distribution network system under strategies S2 and S2' is better than that of strategy S1. This is because strategies S2 and S2' take into account the short-term overload capacity of the intelligent soft switch, while strategy S1 only performs rapid recovery when the capacity of the intelligent soft switch is greater than the recovery load. In addition, compared with strategy S2, since strategy S2' performs rapid recovery in any fault scenario and determines the recovery of the load based on the maximum overload operation time of the intelligent soft switch and the overload elimination time of the intelligent soft switch, the system reliability index under strategy S2' is further improved.

[0218] Figure 7 It is further shown that due to the consideration of the short-term overload capacity of the intelligent soft switch, the number of rapid recovery of the intelligent soft switch under strategies S1, S2, and S2' increases in turn. In order to facilitate the analysis and give full play to the role of the intelligent soft switch in improving the reliability of the flexible interconnected distribution network, strategy S2' is adopted in the following scenarios.

[0219] 5.5 Analysis of the impact of SOP capacity on the reliability of flexible interconnected distribution network

[0220] The SOP capacity is set to 60%, 80%, 100%, 120%, 140%, 160%, 180%, and 200% of the original (2MVA) to analyze the impact of SOP capacity changes on the reliability of the flexible interconnected distribution network. The reliability changes of the flexible interconnected distribution network under different SOP capacities are shown in Figure 2. Figure 8 shown.

[0221] Depend on Figure 8 It can be seen that with the continuous increase of SOP capacity, the reliability of flexible interconnected distribution network continues to improve (I ASAI Continuously rising, I SAIDI When the SOP capacity is 2MVA, it can be seen from Table 3 and Table 5 that although the power outage time of some load points in the flexible interconnected distribution network is still higher than that of the "closed-loop design, open-loop operation" distribution network, considering the effect of SOP rapid transfer on reducing the power outage time of other load points, the overall situation (such as Figure 8 As shown in the figure, the improvement effect of SOP fast transfer on the reliability of flexible interconnected distribution network has basically completely offset the negative impact of reliability caused by the expansion of fault set; when the SOP capacity is increased to 4MVA, the reliability of flexible interconnected distribution network will no longer change, that is, the SOP capacity of 4MVA can basically meet the requirements of fast load transfer under various fault scenarios.

[0222] 5.6 Multi-stage restoration process of flexible interconnected distribution network

[0223] In order to reflect the effective consideration of the multi-stage recovery process by the method of the present invention, it is compared with the single-stage network reconstruction method. In the scenario where the DG capacity is 1.5MW, the load recovery process after the fault is as follows: Figures 9-10 The reliability evaluation results of the flexible interconnected distribution network under the two methods are shown in Table 8.

[0224] Table 8 Comparison of the results of the method of the present invention and single-stage network reconstruction

[0225]

[0226] Depend on Figures 9-10 It can be seen that under different fault scenarios, compared with the single-stage network reconstruction method, the method of the present invention comprehensively considers the rapid recovery of intelligent soft switches, upstream recovery of fault points, switching recovery of tie switches and recovery of island operation, effectively reflecting the multi-stage recovery process after the fault, making the reliability assessment results of the flexible interconnected distribution network more in line with the actual situation and the requirements of "DL / T 1563-2016 Guidelines for Reliability Assessment of Medium Voltage Distribution Networks", and can provide more refined guidance for the planning and construction of flexible interconnected distribution networks.

[0227] It can be seen from Table 8 that the reliability evaluation results obtained based on the proposed method are significantly better than those obtained based on the single-stage network reconstruction method. SAIDI and I EENS Compared with the single-stage network reconstruction method, the reductions were 6.595% and 7.029%, respectively. This is mainly because the single-stage network reconstruction method cannot take into account the rapid transfer of SOP and does not distinguish between upstream recovery, tie switch transfer and island operation.

[0228] If the above method is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0229] In another embodiment, a flexible interconnected distribution network fault recovery and reliability assessment is also provided, including one or more processors, a memory and one or more programs stored in the memory, wherein the one or more programs include instructions for executing the above method.

[0230] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes. The schemes in the embodiments of the present invention may be implemented in various computer languages, for example, object-oriented programming language Java and literal scripting language JavaScript, etc.

[0231] The preferred specific embodiments of the present invention are described in detail above. It should be understood that a person skilled in the art can make many modifications and changes based on the concept of the present invention without creative work. Therefore, any technical solution that can be obtained by a person skilled in the art through logical analysis, reasoning or limited experiments based on the concept of the present invention on the basis of the prior art should be within the scope of protection determined by the claims.

Claims

1. A method for fault recovery and reliability assessment of a flexible interconnected distribution network, characterized in that: The following steps are involved: Obtain basic parameters and reliability parameters of the distribution network, establish an intelligent soft switch equivalent model for fault recovery and reliability assessment, and construct a node-branch status association relationship for the flexible interconnected distribution network; Considering the power recovery constraint and short-term overload capacity of the intelligent soft switch, a fast recovery model of the intelligent soft switch for flexible interconnected distribution network is established. Based on the node-branch state association relationship of the flexible interconnected distribution network and the intelligent soft switch fast recovery model, a multi-stage recovery process is considered, constraints are constructed, and a mixed integer linear programming model for fault recovery and reliability evaluation of the flexible interconnected distribution network is established. The mixed integer linear programming model takes the minimum average power outage time of the system as the objective function; Solving the mixed integer linear programming model to obtain a fault recovery strategy and reliability evaluation result of the flexible interconnected distribution network; The intelligent soft switch equivalent model is expressed as: The node-branch state association relationship of the flexible interconnected distribution network is expressed as: Where: is a 0-1 variable or parameter, indicating the state of node i. If it is in a power outage state, otherwise It is a 0-1 variable or parameter, indicating the state of branch ij. If it is in a power-off state, otherwise is a 0-1 variable or parameter, indicating the switch status of the branch ij node i or j. If it is in the open state, otherwise The subscripts ω and τ represent the source / load scenario and different stages, respectively. Ψ Sc and T Respectively represent the source / load scenario set and the stage set, and Ψ T ={τ FB ,τ LI ,τ FT ,τ UR ,τ TT ,τ IO }, τ FB , τ LI , τ FT , τ UR , τ TT , τ IO They represent fault blocking, fault location isolation, intelligent soft switch fast recovery, fault point upstream recovery, tie switch switching recovery and island operation recovery stages respectively; the superscript μν represents the fault scenario, F.F SOP and F S ' OP They represent the fault scenario set, intelligent soft switch fault scenario set and intelligent soft switch function fault scenario set respectively; the superscript κ is the switch type, K is the switch set, κ N , κ SOP , κ CB , κ LS Respectively represent no switch, intelligent soft switch equivalent switch, circuit breaker and load switch. Β SOP is the intelligent soft switch branch set; Β is the branch set.

2. The method for fault recovery and reliability assessment of a flexible interconnected distribution network according to claim 1, characterized in that: The intelligent soft switch fast recovery model is constructed based on the intelligent soft switch recovery power constraint and the intelligent soft switch short-time overload capacity constraint. The intelligent soft switch short-time overload capacity constraint is characterized by the power outage load recovery situation determined by combining the maximum overload operation time and overload elimination time of the intelligent soft switch when the load to be restored is greater than the capacity of the intelligent soft switch itself.

3. The method for fault recovery and reliability assessment of a flexible interconnected distribution network according to claim 2, characterized in that: The intelligent soft switch recovery power constraint is expressed as: Where: are the active and reactive powers of the intelligent soft-switching converter at node m or n respectively; is the intelligent soft switch capacity on branch mn; is a 0-1 variable or parameter, indicating the state of node m or n. If it is in a power-off state, otherwise It is a 0-1 variable or parameter, indicating the state of branch mn. If it is in a power-off state, otherwise The superscript μν indicates the fault scenario, Β SOP is the set of intelligent soft switch branches; the subscript τ represents different stages, Ψ T represents the set of stages, τ FB Indicates the fault blocking stage.

4. The method for fault recovery and reliability assessment of a flexible interconnected distribution network according to claim 2, characterized in that: The short-time overload capacity constraint of the intelligent soft switch is expressed as: Where: The operating time at maximum overload and overload elimination time After logical judgment, the power outage time of load point i under fault rapid recovery; express Load outage time under certain conditions; express Load power outage time under the condition; F SOP N represents the intelligent soft switch fault scenario set; LP is a set of load points.

5. The method for fault recovery and reliability assessment of a flexible interconnected distribution network according to claim 4, characterized in that: Said Load outage time under the condition It is expressed as: Where: is the state of load point i when the intelligent soft switch is not considered to restore the power constraint; and They are respectively the fault location isolation time and the fault repair time, τ FT Indicates the intelligent soft switch fast recovery stage.

6. The method for fault recovery and reliability assessment of a flexible interconnected distribution network according to claim 4, characterized in that: Said Load outage time under the condition It is expressed as: Where: is the state of load point i when the intelligent soft switch is not considered to restore the power constraint; and They are respectively the fault location isolation time and the fault repair time, τ FB , τ FT They represent the fault blocking stage and the intelligent soft switch fast recovery stage respectively.

7. The method for fault recovery and reliability assessment of a flexible interconnected distribution network according to claim 1, characterized in that: The constructed constraints include fault scenario setting constraints, node-branch state association constraints, fault blocking constraints, fault isolation constraints, fault recovery constraints, load point reliability calculation constraints and system reliability calculation constraints.

8. The method for fault recovery and reliability assessment of a flexible interconnected distribution network according to claim 7, characterized in that: The fault recovery constraints specifically include switch constraints at different recovery stages, intelligent soft switch operation constraints at different recovery stages, distributed power supply operation constraints at different recovery stages, flexible interconnected distribution network operation constraints at different recovery stages and actual power outage time constraints.

9. The method for fault recovery and reliability assessment of a flexible interconnected distribution network according to claim 1, characterized in that: The reliability assessment result includes the value of the reliability assessment index of the flexible interconnected distribution network, and the reliability assessment index of the flexible interconnected distribution network includes the system average power outage frequency, the system average power outage time, the system average power supply reliability rate and the system power shortage amount.

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