Power distribution network island fault recovery and reconstruction method

Abstract

The invention relates to the technical field of power supply network reconstruction, in particular to a power distribution network island fault recovery reconstruction method, which comprises the following steps of: dividing an island power supply area and a main network power supply area, and judging whether a fault area is in the island power supply area; performing network reconstruction on a non-fault area through a POP NSGA-II algorithm; the switch state is coded through binary coding, so that the switch state participating in reconstruction is digitally represented; obtaining a multi-objective optimization problem model by determining a plurality of objective functions and constraint conditions; a Pareto optimization path is recorded through POP, adaptive adjustment is carried out according to conditions, and a clear record of the algorithm optimization process is obtained; and determining an optimal compromise solution from the optimal solution set through a fuzzy set theory. The method has the beneficial effects that the power supply safety and stability are improved, the calculation complexity is optimized, the calculation time is shortened, the reconstruction speed and efficiency are improved, and meanwhile, the safe and stable operation of the network is ensured.

Description

Technical Field

[0001] The invention relates to the technical field of power supply network reconstruction, and in particular to a distribution network island fault recovery and reconstruction method. Background Art

[0002] The fault recovery and reconstruction of the distribution network is a complex process that requires comprehensive consideration of multiple operating indicators and constraints, making the decision-making process extremely complex. Secondly, with the large-scale access of distributed generation (DG) power sources, the optimization problem of the distribution network has become more complicated. The traditional single-power distribution network has been transformed into a multi-power distribution network. Existing algorithms, including traditional mathematical optimization algorithms, heuristic algorithms, and artificial intelligence algorithms, may not be able to effectively cope with these challenges. In addition, the existing technology is insufficient in making full use of distributed power sources for planned island power supply, resulting in insufficient resource utilization. In the algorithm optimization process, the existing methods lack the ability to clearly record the optimization process, making the adjustment and optimization of the algorithm difficult and affecting the convergence speed of the algorithm. Finally, the existing algorithms are also insufficient in computational efficiency and stability. Especially when dealing with complex distribution network reconstruction problems, more efficient algorithms are needed to improve the computational speed and stability. Summary of the invention

[0003] In view of the above problems or problems existing in the prior art, the present invention is proposed.

[0004] Therefore, the purpose of the present invention is to provide a distribution network island fault recovery and reconstruction method, which can solve the current problems faced in distribution network island fault recovery and reconstruction, such as high decision complexity, insufficient algorithm efficiency and stability, insufficient utilization of distributed power sources, and unclear optimization process.

[0005] To solve the above technical problems, the present invention provides the following technical solutions: a method for recovery and reconstruction of an island fault in a distribution network, which comprises dividing an island power supply area and a main network power supply area, and determining whether the fault area is in the island power supply area;

[0006] The network is reconstructed in the non-fault area through the POP NSGA-Ⅱ algorithm;

[0007] The switch state is encoded by binary coding, so that the switch state involved in the reconstruction is digitally represented;

[0008] By determining multiple objective functions and constraints, a multi-objective optimization problem model is obtained;

[0009] By recording the Pareto optimization path through POP and making adaptive adjustments according to the situation, a clear record of the algorithm optimization process is obtained;

[0010] The optimal compromise solution is determined from the optimal solution set through fuzzy set theory.

[0011] As a preferred solution of the distribution network island fault recovery and reconstruction method of the present invention, wherein: the island power supply area is powered by distributed power sources, and the main grid power supply area is powered by the network.

[0012] As a preferred solution of the distribution network island fault recovery and reconstruction method of the present invention, the POP NSGA-Ⅱ algorithm combines the fast convergence characteristics of the NSGA-Ⅱ algorithm and the advantages of the POP record optimal path.

[0013] As a preferred solution of the distribution network island fault recovery and reconstruction method of the present invention, the NSGA-Ⅱ algorithm calculates the crowding distance between individuals in each non-dominated hierarchy to evaluate the distribution density of individuals in the target space.

[0014] As a preferred solution of the distribution network island fault recovery and reconstruction method of the present invention, the POP records the optimization path that records the changes of the Pareto optimal solution of the algorithm during the optimization process. By analyzing the optimization path recorded by the POP, the evolution trend and speed of the algorithm are observed.

[0015] As a preferred solution of the distribution network island fault recovery and reconstruction method of the present invention, the switch state encoding includes a closed state "1" and an open state "0".

[0016] As a preferred solution of the distribution network island fault recovery and reconstruction method of the present invention, there are multiple objective functions, including restoring power supply to faulty loads, reducing the number of switch operations, reducing line losses, controlling voltage deviations, and achieving load balance.

[0017] As a preferred solution of the distribution network island fault recovery and reconstruction method of the present invention, the constraint conditions include the radial structure of the distribution network, flow constraints, voltage deviation range and branch power limit.

[0018] As a preferred solution of the distribution network island fault recovery and reconstruction method of the present invention, the Pareto optimization path uses the POP to record the algorithm optimization process, and adaptively adjusts the selection and mutation operators in the genetic operation according to the evolution situation. When the number of consecutive unchanged POPs reaches a certain value, the selection scale and mutation probability are increased to avoid the algorithm from falling into a local optimum.

[0019] As a preferred solution of the distribution network island fault recovery and reconstruction method of the present invention, the fuzzy set theory calculates the spatial distance between the objective function value of each solution and the ideal value, and selects the solution with the smallest distance as the optimal compromise solution.

[0020] Beneficial effects of the present invention: The present invention forms an electric island to continuously supply power to non-fault power outage areas, realizes maximum resource utilization, and optimizes the path through POP records. On the one hand, the evolution can be stopped in time to reduce redundant calculations; on the other hand, the selection and mutation operators in the genetic operation are adaptively adjusted according to the evolutionary situation to accelerate the convergence speed. The fast non-dominated sorting genetic algorithm is used to perform hierarchical classification based on the dominance hierarchy relationship of individuals, and the crowding distance is defined. The shared virtual fitness is replaced by evaluating the density distribution of adjacent individuals in the same layer to ensure uniform distribution of the frontier. In addition, there is no need to determine the shared fitness value, which reduces the computational complexity and improves the computational efficiency and stability of the algorithm. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work. Among them:

[0022] Figure 1 The overall process diagram of the distribution network island fault recovery and reconstruction method is shown in FIG. DETAILED DESCRIPTION

[0023] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0024] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0025] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0026] Example 1

[0027] Reference Figure 1 , is an embodiment of the present invention, which provides a distribution network island fault recovery and reconstruction method, which can solve the current problems of high decision-making complexity, insufficient algorithm efficiency and stability, insufficient utilization of distributed power sources, and unclear optimization process in distribution network island fault recovery and reconstruction.

[0028] Specifically, the island power supply area and the main grid power supply area are divided to determine whether the fault area is in the island power supply area;

[0029] The network is reconstructed in the non-fault area through the POP NSGA-Ⅱ algorithm;

[0030] The switch state is encoded by binary coding, so that the switch state involved in the reconstruction is digitally represented;

[0031] By determining multiple objective functions and constraints, a multi-objective optimization problem model is obtained;

[0032] By recording the Pareto optimization path through POP and making adaptive adjustments according to the situation, a clear record of the algorithm optimization process is obtained;

[0033] The optimal compromise solution is determined from the optimal solution set through fuzzy set theory.

[0034] It should be noted that before dividing the island power supply area and the main grid power supply area, data is read in first. The data includes parameters of each part of the network, the structure of the network after fault isolation, the status of circuit breakers and interconnecting switches, the output of distributed power sources, the capacity of feeders at all levels, and the total amount of power-off load.

[0035] Furthermore, the island power supply area is powered by distributed power sources, and the main grid power supply area is powered by reconstructing the network.

[0036] It should be noted that in the island power supply area, distributed power sources are used to provide power to the island, and a part of the power-lost load is restored first; in the main grid power supply area, the network is reconstructed to restore as much of the power-lost load as possible, and the island power supply area maintains stable operation through a simple genetic algorithm.

[0037] Furthermore, the POP NSGA-Ⅱ algorithm combines the fast convergence characteristics of the NSGA-Ⅱ algorithm and the advantages of the POP record optimal path.

[0038] Furthermore, the NSGA-Ⅱ algorithm calculates the crowding distance between individuals within each non-dominated level to evaluate the distribution density of individuals in the target space.

[0039] Furthermore, the POP record optimization path records the changes in the Pareto optimal solution of the algorithm during the optimization process. By analyzing the optimization path recorded by POP, the evolution trend and speed of the algorithm can be observed.

[0040] Furthermore, the switch state encoding includes a closed state "1" and an open state "0".

[0041] It should be noted that the switch state coding needs to select the switches participating in the reconstruction according to the reconstructed feeders, and encode such switches. The feeders participating in the reconstruction are determined according to the region and the relationship between the total amount of power-off load and the capacity of the feeders at this level and the first-level feeders. In the main grid power supply area, when the capacity of the feeders at this level is greater than the power-off load capacity, there is no need to consider adding the first-level feeders. Otherwise, the first-level feeders need to be considered.

[0042] Furthermore, multiple objective functions include restoring power supply to faulty loads, reducing the number of switch operations, reducing line losses, controlling voltage deviations, and achieving load balance.

[0043] Furthermore, the constraints include the radial structure of the distribution network, power flow constraints, voltage deviation range and branch power limitations.

[0044] It should be noted that after obtaining the objective function and constraints, it is necessary to deal with infeasible solutions. The forward and backward method is used to calculate the power flow, which avoids large-scale matrix operations and converges quickly. The constraint values ​​of various solutions are obtained by power flow calculation, and then the individuals that do not meet the conditions are eliminated.

[0045] Furthermore, the Pareto optimization path uses POP to record the algorithm optimization process and adaptively adjusts the selection and mutation operators in the genetic operation according to the evolutionary situation. When the number of consecutive unchanged POPs reaches a certain value, the selection scale and mutation probability are increased to prevent the algorithm from falling into a local optimum.

[0046] It should be noted that the calculation of POP requires the calculation of non-dominated sorting and crowding distance of the population, in which the individuals are hierarchically classified according to their dominance levels, and the dominance relationship between individuals is defined as follows:

[0047]

[0048] Among them, f i (x) is the i-th objective function, x is a feasible solution, x is a non-dominated solution, x′ is a dominated solution, and x dominates x′. Non-dominated liberation is in the first layer, which is the optimal solution set. Repeat the stratification steps in the remaining individuals to obtain new non-dominated liberation in the second layer, and so on. Then, crowding distance is used in each layer instead of virtual degree value. The crowding distance is defined as follows:

[0049]

[0050] where f[i] m is the mth objective function value of the ith individual. Update the Pareto optimization path POP according to the change of the optimal solution level. Define the n+1th Pareto optimization direction value T n+1 for:

[0051]

[0052] Among them, C (n+1)i is the i-th chromosome in the optimal solution level when it evolves to the n+1th time. According to the change of the number of individuals in the optimal solution set and the optimization direction value T n+1 , update POP. The formula is as follows:

[0053]

[0054] According to the number of times POP changes continuously, the selection scale is adjusted. When the number of times POP does not change continuously reaches a certain value, the selection scale is appropriately increased to avoid falling into the local optimum. Then a multi-point crossover operation is used to generate offspring. When performing mutation operations, when the number of times POP does not change continuously reaches a certain value, the mutation probability is increased until the mutation probability is twice the initial probability, the algorithm stops, avoiding premature algorithm maturation.

[0055] At this time, the elite strategy is used to obtain a new generation of parents, where the elite strategy refers to merging the generated offspring with the previous generation of parents, and then performing a fast non-dominated sort, starting with individuals with high dominance levels, until the population size reaches the number of the previous generation, achieving a probability of 1 for the optimal individual to be retained, which is a necessary condition for the genetic algorithm to converge with a probability of 1. POP can reflect the maturity of the algorithm. When the number of consecutive unchanged POPs reaches a specified maximum value, the genetic algorithm stops. If not satisfied, the genetic operation must be repeated, that is, to determine whether the POP stop condition is met. If not satisfied, the switch participating in the reconstruction is selected again for encoding, and if satisfied, proceed to the next step.

[0056] Furthermore, fuzzy set theory calculates the spatial distance between the objective function value of each solution and the ideal value, and selects the solution with the smallest distance as the optimal compromise solution.

[0057] In summary, the present invention forms an electric island to continuously supply power to non-fault power outage areas, realizes maximum resource utilization, and optimizes the path through POP records. On the one hand, it can stop evolution in time to reduce redundant calculations; on the other hand, it adaptively adjusts the selection and mutation operators in the genetic operation according to the evolutionary situation to accelerate the convergence speed. It also uses a fast non-dominated sorting genetic algorithm to perform hierarchical classification based on the dominance level relationship of individuals, defines the crowding distance, and replaces the shared virtual fitness by evaluating the density distribution of adjacent individuals in the same layer, ensuring uniform distribution of the frontier. In addition, there is no need to determine the shared fitness value, which reduces the computational complexity and improves the computational efficiency and stability of the algorithm.

[0058] Importantly, it should be noted that the construction and arrangement of the present application shown in a plurality of different exemplary embodiments are only exemplary. Although only a few embodiments are described in detail in this disclosure, it should be readily understood by those who refer to this disclosure that many modifications are possible without substantially departing from the novel teachings and advantages of the subject matter described in the application (e.g., mounting arrangements, use of materials, color, changes in orientation, etc.). For example, the element shown as integrally formed may be composed of a plurality of parts or elements, the position of the element may be inverted or otherwise changed, and the nature or number or position of the discrete element may be altered or changed. Therefore, all such modifications are intended to be included within the scope of the present invention. The order or sequence of any process or method steps may be changed or reordered according to an alternative embodiment. In the claims, any "bracket plus function" clause is intended to cover the structure of the execution function described herein, and is not only structurally equivalent but also equivalent structure. Without departing from the scope of the present invention, other replacements, modifications, changes and omissions may be made in the design, operating conditions and arrangement of the exemplary embodiments. Therefore, the present invention is not limited to a specific embodiment, but extends to a variety of modifications that still fall within the scope of the appended claims.

[0059] Additionally, in an effort to provide a concise description of example embodiments, all features of an actual implementation may not be described.

[0060] It should be understood that in the development of any actual implementation, as in any engineering or design project, numerous implementation-specific decisions may be made. Such a development effort may be complex and time-consuming, but for those of ordinary skill having the benefit of this disclosure, the development effort will be a routine task of design, fabrication, and production without undue experimentation.

[0061] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A method for recovery and reconstruction of a distribution network island fault, characterized in that: include, Divide the island power supply area and the main grid power supply area to determine whether the fault area is in the island power supply area; The network is reconstructed in the non-fault area through the POP NSGA-Ⅱ algorithm; The switch state is encoded by binary coding, so that the switch state involved in the reconstruction is digitally represented; By determining multiple objective functions and constraints, a multi-objective optimization problem model is obtained; By recording the Pareto optimization path through POP and making adaptive adjustments according to the situation, a clear record of the algorithm optimization process is obtained; The optimal compromise solution is determined from the optimal solution set through fuzzy set theory.

2. The method for recovery and reconstruction of a distribution network island fault according to claim 1, characterized in that: The island power supply area is powered by distributed power sources, and the main grid power supply area is powered by reconstructing the network.

3. The method for recovery and reconstruction of a distribution network island fault according to claim 2, characterized in that: The POP NSGA-Ⅱ algorithm combines the fast convergence characteristics of the NSGA-Ⅱ algorithm and the advantages of the POP record optimal path.

4. The method for recovery and reconstruction of a distribution network island fault according to claim 2, characterized in that: The NSGA-II algorithm calculates the crowding distance between individuals within each non-dominated level to evaluate the distribution density of individuals in the target space.

5. The method for recovery and reconstruction of a distribution network island fault according to claim 4, characterized in that: The POP record optimization path records the changes of the Pareto optimal solution of the algorithm during the optimization process. By analyzing the optimization path recorded by the POP, the evolution trend and speed of the algorithm are observed.

6. The method for recovery and reconstruction of a distribution network island fault according to any one of claims 3 to 5, characterized in that: The switch state encoding includes a closed state "1" and an open state "0".

7. The method for recovery and reconstruction of a distribution network island fault according to claim 6, characterized in that: The multiple objective functions include restoring power supply to loads that have lost power due to a fault, reducing the number of switch operations, reducing line losses, controlling voltage deviations, and achieving load balance.

8. The method for recovery and reconstruction of a distribution network island fault according to claim 7, characterized in that: The constraints include the radial structure of the power distribution network, power flow constraints, voltage deviation range and branch power limitations.

9. The method for recovery and reconstruction of a distribution network island fault according to any one of claims 7 or 8, characterized in that: The Pareto optimization path uses POP to record the algorithm optimization process and adaptively adjusts the selection and mutation operators in the genetic operation according to the evolution situation. When the number of consecutive unchanged POPs reaches a certain value, the selection scale and mutation probability are increased to avoid the algorithm from falling into a local optimum.

10. The method for recovery and reconstruction of a distribution network island fault according to claim 9, characterized in that: The fuzzy set theory calculates the spatial distance between the objective function value of each solution and the ideal value, and selects the solution with the smallest distance as the optimal compromise solution.

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