Flexible interconnected power distribution network power supply recovery method and related device

Abstract

The invention discloses a flexible interconnected power distribution network power supply recovery method and a related device. The method comprises the following steps: establishing a loss model of an energy storage type intelligent soft switch; based on the loss model, a power distribution network power supply recovery model containing the energy storage type intelligent soft switch is constructed, and the power distribution network power supply recovery model comprises a target function with the maximum sum of active loads of recovery nodes and the minimum network loss as targets and comprises a plurality of constraint conditions; the whale optimization algorithm is improved to obtain an improved whale optimization algorithm, and the improved whale optimization algorithm is used for optimizing and solving the power supply recovery model of the power distribution network; after the constraint condition and the loss model are converted through a second-order cone relaxation technology, the power distribution network power supply recovery model is solved through an improved whale optimization algorithm, and an optimal power supply recovery scheme is obtained and used for power supply recovery of the flexible interconnection power distribution network. The problems that in the prior art, an energy storage type intelligent soft switch is few in application in power supply recovery of the power distribution network, and the total recovery load amount is not high are solved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power supply recovery of distribution network, and particularly relates to a power supply recovery method of flexible interconnected distribution network and related device. BACKGROUND

[0002] With the large number of distributed generators (DGs) connected to the power grid, the operation control and power output of the distribution network are greatly challenged. Moreover, the DGs have the characteristics of randomness and uncertainty of output, and the traditional operation mode of the distribution network cannot meet the existing demand, which easily leads to poor power quality and unsatisfactory power supply recovery. Flexible interconnection is one of the important measures for renewable energy consumption of the distribution network. Compared with the traditional distribution network, the flexible interconnected distribution network (FIDN) can efficiently coordinate and control the distributed generators, flexible interconnection devices (FIDs) and reactive power compensation devices, so as to realize the energy interconnection of the system and improve the power supply recovery capability of the distribution network.

[0003] The intelligent soft open point (SOP) is a power electronic device installed in the flexible interconnected distribution network, which can replace the traditional switching device to realize the closed-loop operation in the distribution network, and plays an important role in balancing load flow, improving power quality and optimizing system voltage distribution. The intelligent soft open point is mainly connected by two or more voltage source converters (VSCs), and the back-to-back voltage source converter (B2B VSC) is generally used in the distribution network. When the distribution network is normally operated, the intelligent soft open point usually adopts the PQ-VdcQ control mode, and when the distribution network fails, the port connected to the loss side of the intelligent soft open point will be quickly switched to the V / f control model, thereby providing voltage support and load recovery for the fault area. Fault self-healing is one of the important features of the flexible interconnected distribution network, and under the condition of a large number of distributed generators connected, higher requirements are put forward for the self-healing capability of the distribution network. Moreover, the power supply recovery of the distribution network is the last link of the fault self-healing, so it is of great significance to study the power supply recovery of the distribution network.

[0004] However, considering that the cost of the intelligent soft switch is high, the intelligent soft switch can be combined with an energy storage system (ESS). The soft open point with energy storage (E-SOP) combines the power flow control characteristics of the intelligent soft switch and the charging and discharging characteristics of the energy storage system, can effectively increase the performance of power flow optimization of the distribution network, and the E-SOP has a smaller volume and lower cost than the intelligent soft switch and the energy storage system alone. However, the E-SOP has less application in power supply recovery of the distribution network, and the total amount of recovered load is not high. Therefore, it is urgent to design a flexible interconnected distribution network power supply recovery method based on the E-SOP. SUMMARY

[0005] The present application provides a flexible interconnected distribution network power supply recovery method and related device, which is used to solve the problem that the E-SOP has less application in power supply recovery of the distribution network and the total amount of recovered load is not high in the prior art.

[0006] Therefore, the first aspect of the present application provides a flexible interconnected distribution network power supply recovery method, which comprises:

[0007] establishing a loss model of the E-SOP, wherein the loss model comprises AC / DC converter loss and DC / DC converter loss;

[0008] based on the loss model, constructing a power supply recovery model of the distribution network containing the E-SOP, wherein the power supply recovery model comprises a target function with the maximum sum of active loads of recovery nodes and the minimum network loss as the target, and a plurality of constraint conditions;

[0009] after the constraint conditions and the loss model are processed by the second-order cone relaxation technology, the power supply recovery model is solved by using an improved whale optimization algorithm to obtain an optimal power supply recovery scheme, which is used for flexible interconnected distribution network power supply recovery.

[0010] Optionally, the expression of the loss model is:

[0011] ;

[0012] wherein, , , are loss coefficients of different types, is the per-unit value of the apparent power transmitted by the voltage source converter, is the active loss.

[0013] Optionally, the expression of the target function is:

[0014] ;

[0015] ;

[0016] wherein, is a first sub-objective function, is a second sub-objective function, is a system recovery load weight coefficient, is a recovery coefficient at node , and ∈[0,1], is a set of nodes to be recovered, is a set of all branches in the system, is a resistance of branch , is a current value on branch , is an active power at node i, is a loss generated by the energy storage type intelligent soft switch at node .

[0017] Optionally, the constraint conditions include: intelligent soft switch constraints, energy storage system constraints, system power flow constraints, and safe operation constraints.

[0018] The intelligent soft switch constraints include: active power balance constraints, loss constraints, and first capacity constraints.

[0019] The energy storage system constraints include: power balance constraints, charge and discharge constraints, and second capacity constraints.

[0020] Optionally, the improved whale optimization algorithm includes:

[0021] The population is initialized by Logistic chaotic mapping, and an adaptive weight factor is introduced to dynamically adjust the position update strategy.

[0022] Optionally, the transformation processing of the constraint conditions and the loss model by the second-order cone relaxation technology includes:

[0023] The constraint conditions are transformed into a mixed integer second-order cone programming model by the second-order cone relaxation technology;

[0024] The loss model is transformed into a second-order cone form by using the method of variable substitution and relaxation.

[0025] Optionally, it also includes: solving the loss model in the second-order cone form by using the mathematical tool CPLEX.

[0026] The second aspect of the present application provides a flexible interconnected power distribution network power supply recovery system, the system comprising:

[0027] A building unit is configured to build a loss model of the energy storage type intelligent soft switch, the loss model comprising AC / DC converter loss and DC / DC converter loss;

[0028] A building unit is configured to build a power distribution network power supply recovery model containing the energy storage type intelligent soft switch based on the loss model, the power distribution network power supply recovery model comprising an objective function with the maximum recovery load and the minimum network loss as the target, and a plurality of constraint conditions;

[0029] A solving unit is configured to solve the power distribution network power supply recovery model by using an improved whale optimization algorithm after the constraint conditions and the loss model are processed by a second-order cone relaxation technique, to obtain an optimal power supply recovery scheme for flexible interconnected power distribution network power supply recovery.

[0030] The third aspect of the present application provides a flexible interconnected power distribution network power supply recovery device, the device comprising a processor and a memory:

[0031] The memory is configured to store program code and transmit the program code to the processor;

[0032] The processor is configured to execute the steps of the flexible interconnected power distribution network power supply recovery method according to the instructions in the program code.

[0033] The fourth aspect of the present application provides a computer readable storage medium for storing program code, the program code being used to execute the flexible interconnected power distribution network power supply recovery method of the first aspect.

[0034] From the above technical solutions, the present application has the following advantages:

[0035] The flexible interconnected power distribution network power supply recovery method provided by the application firstly constructs a loss model of an energy storage type intelligent soft switch. The energy storage type intelligent soft switch has the advantages of smaller size and lower cost, and can provide excellent regulation capacity. Then, a multi-objective optimization model is constructed, and the objectives include maximizing the recovered load, minimizing the network loss, or maximizing the power supply reliability. Subsequently, an improved intelligent optimization algorithm (such as the IWOA algorithm) is used to solve the optimization model, thereby obtaining a preliminary power supply recovery scheme. Then, the variables in the preliminary scheme are substituted into a second-order cone optimization model, and the power flow distribution is accurately calculated and optimized to ensure that the scheme can meet all the operating constraint conditions, and further improve the economy and stability of the scheme. The method of the application has achieved a breakthrough in the power supply recovery capability of the power distribution network, and solved the problems of less application of the energy storage type intelligent soft switch in the power supply recovery of the power distribution network and low total amount of recovered load in the prior art. BRIEF DESCRIPTION OF DRAWINGS

[0036] In order to more clearly illustrate the technical solutions in the embodiments of the application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or the prior art description. Obviously, the drawings in the following description are only some embodiments of the application, and for those skilled in the art, other drawings can also be obtained from these drawings without creative labor.

[0037] Figure 1 The flowchart of the flexible interconnected power distribution network power supply recovery method provided by the embodiment of the application;

[0038] Figure 2 The basic structure of the E-SOP in the embodiment of the application;

[0039] Figure 3a 、 Figure 3b 、 Figure 3c The optimization results of each algorithm on the test function in the embodiment of the application;

[0040] Figure 4 The power supply recovery flowchart based on the E-SOP in the embodiment of the application;

[0041] Figure 5 The structural diagram of the flexible interconnected power distribution network power supply recovery system provided by the embodiment of the application. DETAILED DESCRIPTION

[0042] In order to make the application purposes, features and advantages of the present application more obvious and easy to understand, the technical solutions in the embodiments of the present application will be described clearly and completely below in conjunction with the drawings of the embodiments of the present application. Obviously, the embodiments described below are only a part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative efforts fall within the scope of the present application.

[0043] The present application mainly proposes a flexible interconnected power distribution network power supply recovery method based on energy storage type SOP to improve the fault recovery effect of the flexible interconnected power distribution network. The method fully considers the loss model of E-SOP, and solves the load recovery model by setting an improved whale optimization algorithm combined with a second-order cone programming method. The results obtained by the present application are more scientific and more accurate.

[0044] Please refer to Figure 1 The flexible interconnected power distribution network power supply recovery method provided in the embodiments of the present application comprises:

[0045] Step 101, a loss model of the energy storage type intelligent soft switch is established, and the loss model comprises AC / DC converter loss and DC / DC converter loss.

[0046] It should be noted that, referring to Figure 2 The embodiments take E-SOP as the basis to specifically describe the process of the present application, as follows:

[0047] The operation frequency of the traditional tie switch is limited and the flexibility is low, and it is difficult to quickly realize the power flow distribution control, while using E-SOP to replace the tie switch can realize continuous adjustment of power between feeders, thereby improving the safety of the power distribution network. The E-SOP mainly consists of three important components: AC / DC converter, ESS and DC / DC converter. Since the E-SOP is the same as the traditional SOP, both are power electronic devices, so corresponding losses will be generated during operation.

[0048] Define a, a0, a1 as different types of loss coefficients, S as the per-unit value of VSC transmitted apparent power, is the active loss. The loss model of the VSC can be approximately equal to a quadratic function mathematical model, as shown in the following formula:

[0049] ;

[0050] Define and as the DC / DC converter loss and the AC / DC converter loss, respectively, and active power transmitted by AC / DC converter and DC / DC converter respectively, S SOP apparent power of AC / DC converter. Then the loss of AC / DC converter and DC / DC converter in E-SOP can be expressed as follows:

[0051] ;

[0052] wherein, , , is the loss coefficient of DC / DC converter; , , and is the loss coefficient of AC / DC converter; is the active power of SOP, is the reactive power of SOP.

[0053] It can be understood that step 101 establishes the loss model of E-SOP, and the loss composition and calculation method of AC / DC converter and DC / DC converter in operation are determined, which lays a foundation for subsequent comprehensive consideration of the operation loss of E-SOP for power restoration strategy optimization, so that the constructed power restoration scheme is more in line with the actual operation condition, and the economy of system operation can be considered while the power restoration effect is ensured.

[0054] Step 102, based on the loss model, a power distribution network power restoration model containing an energy storage type intelligent soft switch is constructed, and the power distribution network power restoration model includes an objective function taking the sum of active loads of restoration nodes and the minimum network loss as the target, and a plurality of constraint conditions.

[0055] It should be noted that α i is the system restoration load weight coefficient, λ i is the restoration coefficient of node i, and λ i ∈[0,1]. Ω n is the set of nodes to be restored, Ω b is the set of all branches in the system. r ij is the resistance of branch ij, I ij is the current value on branch ij. is the active power at node i, is the loss generated by E-SOP at node i. E-SOP can supply power to the power loss area during the fault of power distribution network, but at the same time, the corresponding loss will also be generated in E-SOP, so the objective function taking the sum of active loads of restoration nodes and the minimum network loss as the target is needed, and the expression of the objective function is as follows.

[0056] ;

[0057] ;

[0058] In one embodiment, the constraints include: intelligent soft switch constraints, energy storage system constraints, system power flow constraints and safe operation constraints; wherein the intelligent soft switch constraints include: active power balance constraints, loss constraints and first capacity constraints; the energy storage system constraints include: power balance constraints, charge and discharge constraints and second capacity constraints.

[0059] It should be noted that the E-SOP needs to follow the constraints of the SOP and the ESS during operation. In the direction of the E-SOP output power is positive, and its constraint conditions are as follows:

[0060] 1) Intelligent soft switch (SOP) constraints include: active power balance constraints, loss constraints and capacity constraints;

[0061] Define i, j as the node number of the power distribution system connected by the SOP, 、 、 、 are the active power and reactive power output by the VSC, respectively; and are the upper and lower bounds of the VSC output reactive power, respectively; and are the i, j port capacities of the VSC, and are the loss coefficients of the AC / DC converter. The active power balance constraints, loss constraints and capacity constraints of the SOP are represented as follows:

[0062] ;

[0063] ;

[0064] ;

[0065] ;

[0066] 2) Energy storage system (ESS) constraints include: power balance constraints, charge and discharge constraints, and capacity constraints;

[0067] Define β c and β dc are the charge and discharge flags, respectively. When β c = 1, it indicates that the ESS is in charging state, and when β dc = 1, it indicates that the ESS is in discharging state. 、 are the charge and discharge power of the ESS, is the amount of electricity of the ESS at time t, , These represent the upper and lower limits of the battery capacity, δ c and δ dc These represent the efficiency values ​​for charging and discharging, respectively. The constraints of the ESS (Efficiency Limiting System) are divided into power balance constraints, charge / discharge constraints, and capacity constraints, as shown below:

[0068] ;

[0069] ;

[0070] ;

[0071] ;

[0072] ;

[0073] 3) System power flow constraints;

[0074] Define V i Let P be the voltage at node i. i and Q i Inject the sum of active and reactive power at node i, x ij P is the reactance on branch ij. ij and Q ij Let be the active and reactive power on branch ij. and Let represent the active and reactive power of the distributed power source at node i. Let be the reactive power at node i. and Let be the active and reactive power of E-SOP at node i. Then the system power flow constraints can be expressed as follows:

[0075] ;

[0076] ;

[0077] ;

[0078] ;

[0079] ;

[0080] ;

[0081] 4) System safety operation constraints;

[0082] Define V i,max and V i,min Let I be the upper and lower limits of the voltage at node i, respectively.i,max and I i,min are the upper and lower limits of the current at node i, respectively. Then the system security operation constraints can be expressed as follows:

[0083] ;

[0084] ;

[0085] It can be understood that step 102 aims to solve the optimal power supply recovery scheme by establishing a mixed integer programming model considering the above constraints, with the optimization objectives of minimizing network loss and maximizing the amount of recovered load. The model takes the switch state variables, distributed power output, power transmission of flexible interconnection devices, etc. as decision variables, and solves the model by calling a professional mathematical optimization solver, so as to determine how to reasonably adjust the network topology structure and the operation state of each distributed power supply and flexible interconnection device after the fault occurs, in order to achieve effective power supply recovery for the non-fault power failure area, while ensuring the safe and stable operation of the entire distribution network during and after the recovery process.

[0086] Step 103, after transforming the constraints and loss model by the second-order cone relaxation technique, the improved whale optimization algorithm is used to solve the distribution network power supply recovery model to obtain the optimal power supply recovery scheme for flexible interconnection distribution network power supply recovery.

[0087] In one embodiment, the improvement of the improved whale optimization algorithm in step 103 includes: initializing the population by Logistic chaotic mapping, and introducing an adaptive weight factor to dynamically adjust the position update strategy.

[0088] It should be noted that the whale optimization algorithm has the advantages of simple parameters and good optimization ability, but it is prone to local optimization. Therefore, the present application improves the Whale Optimization Algorithm (WOA) by using Logistic chaotic mapping and position update weight strategy, thereby improving the ability of WOA algorithm to jump out of local optimization, so as to ensure that the WOA algorithm can effectively handle the power supply recovery problem of the distribution network. The improvement process of the whale optimization algorithm includes:

[0089] Define k as the branch parameter, z(t) as the original value, z(t+1) as the output value of the Logistic chaotic mapping, D ’ is the distance between the whale and the optimal solution, b is the spiral parameter, l is a random number between -1 and 1, X(t) is the position of the whale, X p (t) is the position of the current optimal solution, A is the coefficient vector, D is the enclosing step, and ω is the adaptive weight factor. Then the improvement strategy can be expressed as follows:

[0090] ;

[0091] ;

[0092] ;

[0093] ;

[0094] and using , , The three test functions are used to verify the performance of the IWOA algorithm. From Figure 3a , Figure 3b , Figure 3c It can be seen that the improved whale optimization algorithm (IWOA) has stronger optimization ability than the WOA algorithm and the particle swarm optimization algorithm (PSO), which shows that the IWOA algorithm has certain feasibility.

[0095] It can be understood that by improving the construction of the whale optimization algorithm, the efficient solution of the subsequent power distribution network power restoration model is used, so that the model can have stronger global optimization ability and convergence speed when dealing with complex power restoration scenarios, thereby better meeting the actual needs of power distribution network power restoration.

[0096] In one embodiment, the transformation of the constraint condition and the loss model in step 103 by the second-order cone relaxation technique includes: converting the constraint condition into a mixed integer second-order cone programming model by the second-order cone relaxation technique; and converting the loss model into a second-order cone form by using a variable substitution and relaxation method

[0097] It should be noted that the power distribution network power restoration problem is converted into a second-order cone model, and the conversion process is as follows:

[0098] ;

[0099] ;

[0100] ;

[0101] ;

[0102] ;

[0103] It is also necessary to convert the loss model of the E-SOP into a second-order cone form, which is performed by using a variable substitution and relaxation method.

[0104] Definition b dc1 , b dc2 , b ad1 and b ad2 are auxiliary variables, then the loss model of AC / DC converter and DC / DC converter in E-SOP can be expressed as follows:

[0105] ;

[0106] ;

[0107] After the above transformation, the power supply restoration problem of distribution network is converted into a second-order cone model, which can be solved by using mathematical tool CPLEX.

[0108] The E-SOP-based power supply restoration flowchart in the embodiment is shown in Figure 4 , and the specific restoration steps are as follows:

[0109] Step 1: First, construct the power supply restoration structure based on E-SOP, and input the basic parameters in the system;

[0110] Step 2: Initialize the whale population by using Logistic chaotic mapping, and let the model enter the loop;

[0111] Step 3: Update the coefficient vector A, C, the shrinkage coefficient a and the adaptive weight factor ω;

[0112] Step 4: First, judge whether the probability p is less than 0.5, if not, update the whale position by using the cosine position update weight strategy; if yes, continue to judge the size of the coefficient vector A, if |A| is not less than 1, proceed to the search prey stage, if |A| is less than 1, update the whale position by using the improved bubble net predation method;

[0113] Step 5: Obtain the updated population, and convert the constraint condition into a mixed integer second-order cone model for solving;

[0114] Step 6: Obtain the current optimal output scheme, and judge whether the model reaches the maximum iteration number, if not, re-enter the loop; if yes, output the final optimal power supply restoration scheme.

[0115] Understandably, step 103 transforms the complex nonlinear constraints and loss model in the original problem into a more easily solvable second-order cone form using the second-order cone relaxation technique. Meanwhile, the improved whale optimization algorithm enhances its search capability for the optimal power restoration scheme through strategies such as chaotic population initialization and dynamic adjustment of coefficients and weights. The combination of these two approaches achieves efficient solutions to the power restoration problem in flexible interconnected distribution networks, enabling the rapid identification of the optimal solution that reduces network losses and improves power supply reliability while meeting system operational constraints.

[0116] This invention provides a method for power restoration in a flexible interconnected distribution network. First, a comprehensive analysis is conducted on the network topology, load distribution, distributed generation (DG) output, and operational characteristics of flexible interconnection devices (such as E-SOPs) after a distribution network fault to clarify the fault area and the load to be restored. Based on this, considering system safety constraints such as node voltage range, line power flow limitations, DG output limitations, and E-SOP capacity limitations, a multi-objective optimization model is constructed with the goals of maximizing restored load, minimizing network losses, or maximizing power supply reliability. Subsequently, an improved intelligent optimization algorithm (such as the IWOA algorithm) is used to solve this optimization model to obtain a preliminary power restoration scheme, including the opening and closing states of tie switches, the power transmission direction and magnitude of E-SOPs, and the DG output adjustment strategy. Next, the variables in the preliminary scheme are substituted into a second-order cone optimization model to accurately calculate and optimize the power flow distribution, ensuring that the scheme meets all operational constraints and further improving the scheme's economy and stability. Finally, through comparative analysis with different recovery strategies such as using only tie switches, employing traditional intelligent algorithms (such as PSO and WOA algorithms) combined with second-order cone optimization, the superiority of the proposed method in terms of recovery effect, computational efficiency, and robustness is verified, thus providing an efficient and feasible solution for fault recovery of flexible interconnected distribution networks.

[0117] The above describes a method for restoring power supply to a flexible interconnected distribution network, as provided in an embodiment of the present invention. The following describes a system for restoring power supply to a flexible interconnected distribution network, as provided in an embodiment of the present invention.

[0118] Please see Figure 5 The present invention provides a flexible interconnected power distribution network power restoration system, comprising:

[0119] Unit 201 is used to establish a loss model for energy storage intelligent soft switching. The loss model includes AC / DC converter losses and DC / DC converter losses.

[0120] The construction unit 202 is configured to construct a power distribution network power restoration model containing the energy storage type intelligent soft switch based on the loss model, and the power distribution network power restoration model includes an objective function taking the maximum restored load and the minimum network loss as the target and a plurality of constraint conditions.

[0121] The solving unit 203 is configured to solve the power distribution network power restoration model by using the improved whale optimization algorithm after the constraint condition and the loss model are processed by the second-order cone relaxation technology, so as to obtain an optimal power restoration scheme for the flexible interconnected power distribution network power restoration.

[0122] Further, the embodiment of the present application further provides a flexible interconnected power distribution network power restoration device, and the device comprises a processor and a memory:

[0123] The memory is configured to store program code and transmit the program code to the processor.

[0124] The processor is configured to execute the steps of the flexible interconnected power distribution network power restoration method according to the instructions in the program code.

[0125] Further, the embodiment of the present application further provides a computer readable storage medium, and the computer readable storage medium is configured to store program code, and the program code is configured to execute the flexible interconnected power distribution network power restoration method.

[0126] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the system, device and unit described above can refer to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0127] In the several embodiments of the present application, it should be understood that the disclosed system, device and method can be implemented in other ways. For example, the device embodiments described above are only schematic. The division of the units is only a logical function division. There can be another division manner in actual implementation, for example, a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the displayed or discussed mutual coupling or direct coupling or communication connection between the units can be indirect coupling or communication connection through some interfaces, devices or units, and can be electrical, mechanical or other forms.

[0128] The units described as separate components can or can not be physically separate, and the components shown as units can or can not be physical units, that is, they can be located in one place, or they can be distributed on a plurality of network units. According to actual needs, some or all of the units can be selected to achieve the purpose of the embodiment scheme.

[0129] In addition, each functional unit in each embodiment of the present application can be integrated in one processing unit, or each unit can exist physically, or two or more units can be integrated in one unit. The integrated unit can be realized in the form of hardware or in the form of a software functional unit.

[0130] If the integrated unit is realized 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 such understanding, the technical solutions of the present application, essentially or the part that contributes to the prior art, or all or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium, and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods in each embodiment of the present application. The aforementioned storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a magnetic disk or an optical disk, and various media that can store program codes.

[0131] The above embodiments are only used to illustrate the technical solutions of the present application, rather than limit them; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: it can still modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacement for part of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of each embodiment of the present application.

Claims

1. A method for restoring power supply in a flexible interconnected distribution network, characterized in that, include: A loss model for an energy storage-type intelligent soft switch is established, which includes AC / DC converter losses and DC / DC converter losses. Based on the loss model, a power supply recovery model for a distribution network containing the energy storage intelligent soft switch is constructed. The power supply recovery model for the distribution network includes an objective function that aims to maximize the sum of active loads of the recovery nodes and minimize network losses, as well as several constraints. After transforming the constraints and loss model using the second-order cone relaxation technique, the improved whale optimization algorithm is used to solve the power supply restoration model of the distribution network to obtain the optimal power supply restoration scheme for power supply restoration of flexible interconnected distribution networks.

2. The power supply restoration method for flexible interconnected distribution networks according to claim 1, characterized in that, The expression for the loss model is: ； In the formula, , , For different types of loss coefficients, To transmit the per-unit value of apparent power for voltage source converters. This refers to active power loss.

3. The power supply restoration method for flexible interconnected distribution networks according to claim 1, characterized in that, The expression for the objective function is: ； ； In the formula, For the first sub-objective function, For the second sub-objective function, The system restores the load weighting factor. For nodes The coefficient of recovery at that location, and ∈[0,1], The set of nodes to be restored. For the set of all branches in the system, branch road The resistance, branch road The current value on, Let be the active power at node i. For nodes The losses generated by the energy storage intelligent soft switch.

4. The power supply restoration method for flexible interconnected distribution networks according to claim 1, characterized in that, The constraints include: intelligent soft switching constraints, energy storage system constraints, system power flow constraints, and safe operation constraints; The intelligent soft-switching constraints include: active power balance constraints, loss constraints, and a first capacity constraint. The constraints of the energy storage system include: power balance constraints, charge / discharge constraints, and second capacity constraints.

5. The power supply restoration method for a flexible interconnected distribution network according to claim 1, characterized in that, The improved processing of the improved whale optimization algorithm includes: The population is initialized using a Logistic chaotic mapping, and an adaptive weight factor is introduced to dynamically adjust the position update strategy.

6. The power supply restoration method for a flexible interconnected distribution network according to claim 1, characterized in that, The transformation of the constraint conditions and the loss model using the second-order cone relaxation technique includes: The constraints are transformed into a mixed-integer second-order cone programming model using the second-order cone relaxation technique. The loss model is transformed into a second-order cone form using variable substitution and relaxation methods.

7. The method for restoring power supply to a flexible interconnected distribution network according to claim 6, characterized in that, Also includes: The loss model in the form of a second-order cone was solved using the mathematical tool CPLEX.

8. A flexible interconnected power distribution network power restoration system, characterized in that, include: A modeling unit is established to build a loss model for an energy storage intelligent soft switch, the loss model including AC / DC converter losses and DC / DC converter losses. The construction unit is used to construct a power distribution network recovery model containing the energy storage intelligent soft switch based on the loss model. The power distribution network recovery model includes an objective function aimed at maximizing the recovery load and minimizing network loss, as well as several constraints. The solution unit is used to transform the constraints and the loss model using the second-order cone relaxation technique, and then use the improved whale optimization algorithm to solve the power distribution network power restoration model to obtain the optimal power restoration scheme for power restoration of flexible interconnected distribution networks.

9. A flexible interconnected power distribution network power restoration device, characterized in that, The device includes a processor and a memory: The memory is used to store program code and transmit the program code to the processor; The processor is used to execute the power supply restoration method for flexible interconnected distribution networks according to any one of claims 1-7, based on the instructions in the program code.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium is used to store program code for executing the power supply restoration method for flexible interconnected distribution networks according to any one of claims 1-7.

Images