Power system reliability evaluation method based on Borger division

Abstract

The invention relates to the technical field of power system reliability evaluation, and particularly discloses a power system reliability evaluation method based on Borger partition, and the method comprises the steps: carrying out the permutation and combination of the element states of elements in a to-be-analyzed power system, obtaining a plurality of element state combinations, and taking each element state combination as a system state, constructing a system state space; defining a partial order relationship for each system state, and constructing a Borger structure according to the partial order relationship; the method comprises the following steps of: dividing a Brinell structure into two Brinell substructures on the basis of a bisection method, determining a maximum element and a minimum element of each Brinell substructure, and determining to continuously divide the Brinell substructures or put the Brinell substructures into corresponding system state spaces according to power system operation states of the maximum elements and the minimum elements until a preset division condition is met; determining a target system state through the failure system state space, and evaluating the reliability of the to-be-analyzed power system according to the target system state.

Description

Technical Field

[0001] The present application relates to the technical field of power system reliability assessment, and in particular to a power system reliability assessment method based on Boolean partitioning. Background Art

[0002] With the continuous advancement of the "dual carbon" goal, the number of renewable energy equipment such as wind and light in the power system has increased sharply, causing the power system to become more and more complex. In the power system, each component (the component can be the above-mentioned renewable energy equipment such as wind and light, or it can be an assembly such as a busbar) has two states, one is the normal component state, and the other is the failed component state (the failed component state indicates that the component has failed and can no longer work normally without intervention). Each component is assigned an element state, and the element states corresponding to different components are combined together to form a system state of the power system. Combining different system states of the power system together constitutes the system state space of the power system. Analyzing whether the power system fails in each system state in the system state space is of vital importance to studying the reliability of the power system. However, due to the large number of components in the current power system, the number of system states corresponding to the power system is huge, and the scale of the system state space of the power system is growing exponentially, which poses a huge challenge to the reliability assessment of the power system operation.

[0003] In the prior art, when using the system state space to evaluate the reliability of the power system, either an enumeration method is used to analyze each system state in the system state space one by one, and finally all normal system states or all failed system states are found; or sampling is performed from the system state space according to the probability of occurrence of the system state, and the sampled system state is evaluated to determine whether the system state is a normal system state or a failed system state, and then the reliability of the power system is evaluated based on these system states. However, for the first method, since the system state space of the power system is huge, if the enumeration method is used to evaluate the system states one by one, not only a lot of analysis costs are wasted, but also the analysis efficiency is low; for the second method, the probability of occurrence of high-order system states (i.e., system states in which a large number of components fail at the same time) is often low, resulting in high-order system states being difficult to sample. If the reliability of the power system is evaluated by the sampling method, the reliability obtained will eventually be low in accuracy. Summary of the invention

[0004] In view of this, the present application provides a method for evaluating the reliability of an electric power system based on Boolean partitioning, wherein a Boolean structure is constructed according to the system state corresponding to the electric power system to be analyzed, and then the Boolean structure is continuously partitioned using the dichotomy method. For the Boolean substructures obtained in each partition, it is only necessary to judge the operating state of the electric power system corresponding to the maximum element and the minimum element therein, so as to find the system state that puts the electric power system to be analyzed in a failed system state from the system state space, thereby improving the analysis efficiency. Meanwhile, even for an electric power system to be analyzed with a large number of components, it is possible to quickly find the high-order and low-order system states that put the electric power system to be analyzed in a failed system state from the system state space corresponding to the electric power system to be analyzed, thereby improving the calculation accuracy of the reliability of the subsequent electric power system to be analyzed.

[0005] According to one aspect of the present application, a method for evaluating the reliability of a power system based on Boolean partitioning is provided, comprising:

[0006] Arrange and combine the component state of each component in the power system to be analyzed to obtain multiple component state combinations, and use each component state combination as a system state to construct a system state space of the power system to be analyzed, wherein each system state includes an component state of each component, and the component state is a normal component state or a failed component state;

[0007] Defining a partial order relationship between each system state in the system state space, and constructing a Boolean structure corresponding to the power system to be analyzed according to the partial order relationship;

[0008] Dividing the Boolean lattice structure into two Boolean lattice substructures based on the dichotomy method, determining the maximum element and the minimum element in each Boolean lattice structure respectively, and determining whether to continue dividing the Boolean lattice structure or put it into the corresponding target system state space according to the power system operation state corresponding to the maximum element and the minimum element until a preset division condition is met, wherein the target system state space includes a normal system state space and a failure system state space;

[0009] The target system state is determined through the failed system state space, and the reliability of the power system to be analyzed is evaluated based on the target system state.

[0010] By means of the above technical scheme, the present application provides a method for evaluating the reliability of a power system based on Boolean partitioning. First, the number of components in the power system to be analyzed can be determined, and then each component is assigned a component state, and the component states corresponding to different components in the power system to be analyzed are combined together, that is, a component state combination corresponding to the power system to be analyzed is formed. Each component state combination is regarded as a system state, and the finite set consisting of these system states can be called a system state space. A partial order relationship is defined between various system states in the system state space, and then a Boolean structure corresponding to the power system to be analyzed can be constructed according to the defined partial order relationship. After obtaining the Boolean structure, each Boolean structure can be divided by dichotomy, so that two Boolean lattice substructures are obtained, and the maximum element and the minimum element are found from each Boolean lattice substructure. Further, the power system operating state corresponding to the maximum element and the power system operating state corresponding to the minimum element can be judged, and it can be determined whether to continue to divide the Boolean lattice substructure or put the Boolean lattice substructure into the target system state space according to the judgment result. Here, the target system state space can be a normal system state space or a failure system state space. After multiple divisions, if the preset division conditions are met, it means that the division based on the binary division method has been completed. After that, the system state corresponding to the power system to be analyzed when it is in the failed system state can be further determined through the failed system state space, and each system state in the failed system state space is used as the target system state, and the reliability of the power system to be analyzed is evaluated according to these target system states. The embodiment of the present application constructs a Boolean structure according to the system state corresponding to the power system to be analyzed, and then the Boolean structure is continuously divided by binary division. For the Boolean substructure obtained by each division, it is only necessary to judge the power system operation state corresponding to the maximum element and the minimum element therein, and the system state that makes the power system to be analyzed in the failed system state can be found from the system state space, which can improve the analysis efficiency. At the same time, even for the power system to be analyzed with a large number of components, the high-order and low-order system states that make the power system to be analyzed in the failed system state can be quickly found from the system state space corresponding to the power system to be analyzed, thereby improving the calculation accuracy of the reliability of the subsequent power system to be analyzed.

[0011] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0013] Figure 1 A schematic diagram of a process of a power system reliability assessment method based on Boolean partitioning provided in an embodiment of the present application is shown;

[0014] Figure 2 A schematic diagram of the structure of a third-order Boolean grid provided in an embodiment of the present application is shown;

[0015] Figure 3 A schematic diagram of a process of another power system reliability assessment method based on Boolean partitioning provided in an embodiment of the present application is shown;

[0016] Figure 4 A schematic diagram of the structure of a fifth-order Boolean grid provided in an embodiment of the present application is shown;

[0017] Figure 5 A schematic diagram of a Boolean structure partitioning method based on dichotomy provided in an embodiment of the present application is shown. DETAILED DESCRIPTION

[0018] The present application will be described in detail below with reference to the accompanying drawings and in combination with embodiments. It should be noted that the embodiments and features in the embodiments of the present application can be combined with each other without conflict.

[0019] In this embodiment, a power system reliability assessment method based on Boolean partition is provided. Figure 1 As shown, the method includes:

[0020] Step 101, arrange and combine the component state of each component in the power system to be analyzed to obtain multiple component state combinations, and use each component state combination as a system state to construct the system state space of the power system to be analyzed, wherein each system state includes a component state of each component, and the component state is a normal component state or a failed component state.

[0021] A method for evaluating the reliability of a power system based on Boolean partitioning provided in an embodiment of the present application can quickly divide the system state space corresponding to the power system to be analyzed, find the system state that can make the power system operating state a normal system state, and find the system state that can make the power system operating state a failed system state from the system state space. Here, the normal system state refers to the power system not shedding load, and the failed system state refers to the power system shedding load. For any power system, various components may be included. Here, the component may be equipment in the power system, such as wind, light and other renewable energy equipment, generator equipment, etc.; the component may also be some assembly parts in the power system, such as busbars, etc. For any component, its component state may include two types, one is a normal component state and the other is a failed component state. In the normal component state, the component can work normally; in the failed component state, the component stops working. First, the number of components in the power system to be analyzed can be determined, and then each component is assigned a component state, and the component states corresponding to different components in the power system are combined together, that is, a component state combination corresponding to the power system to be analyzed is formed. For example, if the power system to be analyzed includes n components, then any combination of component states of the power system to be analyzed can be expressed as s = (x1, x2, ... x n ), where x i ∈{1,0},i=1,2,…n,x i =0 means that the component state corresponding to component i is the normal component state, x i =1 means that the component state corresponding to component i is a failed component state, and the number of component state combinations s of the power system to be analyzed is 2 n If each component state is combined as a system state, then the finite set of these system states can be called the system state space.

[0022] Step 102: define a partial order relationship between each system state in the system state space, and construct a Boolean structure corresponding to the power system to be analyzed according to the partial order relationship.

[0023] In this embodiment, a partial order relationship is defined between each system state in the system state space, and then a Boolean structure corresponding to the power system to be analyzed can be constructed according to the defined partial order relationship. Specifically, a natural partial order relationship is defined in the system state space: if for any i=1, 2, ...n, there is s m (i)≤s m+1 (i), then s m Less than or equal to s m+1 , denoted as s m ≤s m+1. Where i represents the number of components in the power system to be analyzed, m represents the order of the system state, and the order of the system state represents the number of failed component states contained in the system state. For example, if a system state contains 5 failed component states, then the system state can be called a fifth-order system state, and all the fifth-order system states can form a fifth-order system state space. In discrete mathematics, when the power system includes n components, the system state space S with a natural partial order forms an n-order Boolean Lattice, denoted as n ,≤>. In the n-order Boolean grid, there is a relationship that the state of the system in the previous layer is greater than the state of the system in the next layer. The structure of the 3rd-order Boolean grid can be as follows Figure 2 As shown, Figure 2 The system states in define the system states of the partial order relation.

[0024] Step 103, based on the dichotomy method, divide the Boolean lattice structure into two Boolean lattice substructures, determine the maximum element and the minimum element in each Boolean lattice substructure respectively, and according to the power system operating state corresponding to the maximum element and the minimum element, determine to continue to divide the Boolean lattice structure or put it into the corresponding target system state space until the preset division condition is met, wherein the target system state space includes a normal system state space and a failure system state space.

[0025] ​In this embodiment, after obtaining the Boolean structure, the Boolean structure can be divided by dichotomy to obtain two Boolean substructures. Here, the number of system states contained in the two Boolean substructures obtained after the division is the same. For the power system, the power system operation state can include two types: one is the normal system state; the other is the failure system state, that is, the load shedding state. In order to find the system state used to analyze the reliability of the power system to be analyzed from each Boolean substructure, further, for any Boolean substructure, the maximum element and the minimum element in the Boolean lattice structure can be determined. For the power system, the power system has the following physical properties: if the component states corresponding to all components in the power system are failure component states, then the operation state corresponding to the power system must also be a failure system state; if the component states corresponding to all components in the power system are normal component states, then the operation state corresponding to the power system must also be a normal system state; if the power system is already in a failure system state, then even if more components fail, then the power system must still be a failure system state; if the power system is already in a normal system state, then even if more components return to normal, then the power system must still be a normal system state. Therefore, it can be stipulated that the maximum element and the minimum element are the system state with the largest number of failed component states (the number is recorded as a) and the system state with the smallest number of failed component states (the number is recorded as b) in the Boolean lattice structure. In this way, when the power system operation states corresponding to the maximum element and the minimum element are both failed system states, the number of failed component states of each system state in the Boolean lattice structure is greater than b, then all the system states in the Boolean lattice structure are system states that make the power system operation state in a failed system state; when the power system operation states corresponding to the maximum element and the minimum element are both normal system states, the number of normal component states of each system state in the Boolean lattice structure is greater than (na), where n represents the number of components in the power system to be analyzed, then all the system states in the Boolean lattice structure are system states that make the power system operation state in a normal system state. This method can make the entire judgment process more efficient. After determining the maximum element and the minimum element in each Boolean lattice structure, we can further judge the power system operating state corresponding to the maximum element and the power system operating state corresponding to the minimum element, and determine whether to continue to divide the Boolean lattice structure or place the Boolean lattice structure into the corresponding target system state space based on the judgment result.Here, when the power system operation states corresponding to the maximum element and the minimum element in the Boolean lattice structure are both normal system states, then the Boolean lattice structure can be placed in the normal system state space; when the power system operation states corresponding to the maximum element and the minimum element in the Boolean lattice structure are both failure system states, then the Boolean lattice structure can be placed in the failure system state space; when the power system operation states corresponding to the maximum element and the minimum element in the Boolean lattice structure are different, then it can be determined to continue to divide the Boolean lattice structure. After multiple divisions, if the preset division conditions are met, it means that the division based on the dichotomy has been completed. It should be noted that the normal system state space stores the system states that make the operation state of the power system to be analyzed the normal system state, and the failure system state space stores the system states that make the operation state of the power system to be analyzed the failure system state.

[0026] Step 104: determine the target system state through the failed system state space, and evaluate the reliability of the power system to be analyzed according to the target system state.

[0027] In this embodiment, the system state corresponding to the power system to be analyzed when it is in the failed system state can be further determined through the failed system state space. Specifically, each system state in the failed system state space can be used as a target system state. The reliability of the power system to be analyzed can then be evaluated based on these target system states.

[0028] By applying the technical solution of this embodiment, first, the number of components in the power system to be analyzed can be determined, and then each component is assigned a component state, and the component states corresponding to different components in the power system to be analyzed are combined together, that is, a component state combination corresponding to the power system to be analyzed is formed. Each component state combination is regarded as a system state, and the finite set composed of these system states can be called the system state space. A partial order relationship is defined between various system states in the system state space, and then the Boolean structure corresponding to the power system to be analyzed can be constructed according to the defined partial order relationship. After obtaining the Boolean structure, each Boolean structure can be divided by dichotomy, so that two Boolean lattice substructures are obtained, and the maximum element and the minimum element are found from each Boolean lattice substructure. Further, the power system operating state corresponding to the maximum element and the power system operating state corresponding to the minimum element can be judged, and it can be determined whether to continue to divide the Boolean lattice substructure or put the Boolean lattice substructure into the target system state space according to the judgment result. Here, the target system state space can be a normal system state space or a failure system state space. After multiple divisions, if the preset division conditions are met, it means that the division based on the dichotomy has been completed. Afterwards, the system state corresponding to the power system to be analyzed when it is in the failed system state can be further determined through the failed system state space, and each system state in the failed system state space is used as the target system state, and the reliability of the power system to be analyzed is evaluated based on these target system states. The embodiment of the present application constructs a Boolean structure according to the system state corresponding to the power system to be analyzed, and then continuously divides the Boolean structure using dichotomy. For the Boolean substructures obtained by each division, it is only necessary to judge the power system operation state corresponding to the maximum element and the minimum element therein, and the system state that makes the power system to be analyzed in the failed system state can be found from the system state space, which can improve the analysis efficiency. At the same time, even for the power system to be analyzed with a large number of components, the high-order and low-order system states that make the power system to be analyzed in the failed system state can be quickly found from the system state space corresponding to the power system to be analyzed, thereby improving the calculation accuracy of the reliability of the subsequent power system to be analyzed.

[0029] In an embodiment of the present application, optionally, before step 103, the method further includes: obtaining a system structure diagram and system parameters corresponding to the power system to be analyzed; based on the system structure diagram and the system parameters, constructing a target DC power flow equation and an optimal load shedding model for the power system to be analyzed; accordingly, after "respectively determining the maximum element and the minimum element in each Boolean lattice structure" in step 103, the method further includes: solving a first load shedding amount of the optimal load shedding model with the target DC power flow equation as a constraint according to the system state corresponding to the maximum element, and determining the power system operating state corresponding to the maximum element according to the first load shedding amount; and, solving a second load shedding amount of the optimal load shedding model with the target DC power flow equation as a constraint according to the system state corresponding to the minimum element, and determining the power system operating state corresponding to the minimum element according to the second load shedding amount.

[0030] In this embodiment, before calculating the operating state of the power system corresponding to the maximum element and the minimum element, the system structure diagram and system parameters corresponding to the power system to be analyzed can be obtained first. Here, the system structure diagram is a diagram used to indicate the connection structure between various components in the power system, and the system parameters can be various original parameters in the power system to be analyzed, such as the failure rate and rated current of the line, and the failure rate and power generation of the generator. Afterwards, the target DC power flow equation and the optimal load shedding model of the power system to be analyzed can be constructed based on the system structure diagram and the system parameters. Specifically, the target DC power flow equation and the optimal load shedding model can be as follows:

[0031] Load shedding model:

[0032]

[0033] Target DC power flow equation:

[0034] T(S)=A(S)(PG-PD+C) formula (2);

[0035]

[0036]

[0037] 0≤C i ≤PD i (i∈ND) formula (5);

[0038]

[0039] Wherein, T(S) is the line active power vector under state S, A(S) is the association matrix between the line active power vector and the node injection power under state S, PG, PD and C are the node generator injection active power vector, node active load vector and node load reduction vector respectively; NG, ND and L are the generator bus set, load bus set and branch set respectively; PG i , PD i , C i and T k (S) are the elements of PG, PD, C and T(S), respectively; PG i and T k (S) limit.

[0040] In the target DC power flow equation, formula (2) and formula (3) are equality constraints; formula (4) to formula (6) are inequality constraints.

[0041] After determining the maximum element and the minimum element in each Boolean lattice structure, the target DC power flow equation and the optimal load shedding model can be used to respectively calculate the power system operating state corresponding to the maximum element and the power system operating state corresponding to the minimum element. Here, the target DC power flow equation is a DC power flow equation related to the structure of the power system to be analyzed. Specifically, according to the system state corresponding to the maximum element, the first load shedding amount of the optimal load shedding model with the target DC power flow equation as a constraint condition can be solved, and further and based on the first load shedding amount, the power system operating state corresponding to the maximum element can be determined. Similarly, according to the system state corresponding to the minimum element, the second load shedding amount of the optimal load shedding model with the target DC power flow equation as a constraint condition can be solved, and further and based on the second load shedding amount, the power system operating state corresponding to the minimum element can be determined. In the prior art, for the enumeration method and the sampling method, it is necessary to use the target DC power flow equation and the load shedding model to calculate the power system operating state under each selected system state, while in the present application, only the system state corresponding to the maximum element and the minimum element needs to be calculated for the power system operating state each time, which can greatly reduce the number of power flow calculations, and can quickly identify which system states make the power system to be analyzed in a normal system state and which system states make the power system to be analyzed in a failed system state, thereby improving the efficiency of identifying the system state.

[0042] Further, as a refinement and extension of the specific implementation of the above embodiment, in order to fully illustrate the specific implementation process of this embodiment, another power system reliability assessment method based on Boolean partition is provided, such as Figure 3 As shown, the method includes:

[0043] Step 201, arrange and combine the component state of each component in the power system to be analyzed to obtain multiple component state combinations, and use each component state combination as a system state to construct the system state space of the power system to be analyzed, wherein each system state includes an component state of each component, and the component state is a normal component state or a failed component state.

[0044] Step 202: divide the system states in the system state space according to the order to obtain each order system state space, wherein the number of failed component states contained in each system state in each order system state space is the same; arrange the system states contained in each order system state space into a row, and arrange each row in descending order of order to obtain the Boolean structure corresponding to the power system to be analyzed.

[0045] In this embodiment, in order to improve the recognition efficiency of the system state in each Boolean lattice substructure and reduce the number of dichotomy divisions, the Boolean structure can be constructed according to certain rules. Specifically, all system states corresponding to the power system to be analyzed can be grouped according to the order to obtain the system state space of each order. Here, for any s∈S, s=(x1,x2,…,x n ), call (x1,x2,…,x n ) is the order of s, that is, the number of failed component states is the order of s. Wherein, S is the system state space, and s is the system state. The set of all system states of order k is called the k-order system state space, that is, the number of failed component states (that is, the number of 1s) corresponding to each system state in the k-order system state space is the same, and is all k. For example, for system state 1, system state 2, and system state 3, assuming that system state 1 contains 3 failed component states and 7 normal component states, system state 2 contains 5 failed component states and 5 normal component states, and system state 3 contains 3 failed component states and 7 normal component states, then system state 1 and system state 3 can be called third-order system states and can be divided into the third-order system state space, while system state 2 can be called fifth-order system state and can be divided into the fifth-order system state space. Afterwards, the system states in the same-order system state space can be arranged in a row. Because there are multiple different-order system state spaces, multiple different rows can be formed. Afterwards, these rows can be arranged in descending order, and the Boolean structure corresponding to the power system to be analyzed can be obtained. For example, the power system to be analyzed includes n elements. Assuming that the rows are adjusted in descending order, the orders corresponding to the adjusted rows can be n, ..., 2, 1, 0 from top to bottom, thereby obtaining the Boolean structure corresponding to the power system to be analyzed.

[0046] Figure 4 A schematic diagram of a Boolean structure provided by an embodiment of the present application is shown. The power system to be analyzed includes a total of 5 elements. First, the system states in the system state space are grouped according to the order, and 6 groups are obtained, corresponding to the first-order system state space to the sixth-order system state space, respectively. These groups (that is, these rows) are sorted in order from large to small according to the order, that is, the group corresponding to the fifth-order system state space is placed at the top, and the group corresponding to the zero-order system state space is placed at the bottom, so as to obtain Figure 4 The Boolean structure shown.

[0047] Step 203: divide the Boolean structure based on the dichotomy method to obtain two Boolean substructures, wherein the number of system states contained in the two Boolean substructures is the same, and the first row and the last row of each Boolean substructure respectively include a system state; the system state in the first row is used as the maximum element, and the system state in the last row is used as the minimum element.

[0048] In this embodiment, after obtaining the Boolean structure, the Boolean structure can be divided by binary division to obtain two Boolean substructures. It should be noted that when the Boolean structure is divided by binary division, it can also be divided according to the following rules. For example, when the Boolean structure is divided by binary division, it is required that the number of system states contained in the two Boolean substructures obtained by each division is equal, and the first row and the last row of each Boolean substructure only include one system state. For example, Figure 5 As shown, a schematic diagram of a Boolean structure partitioning method is given.

[0049] In each Boolean lattice structure obtained by the above method, since there is a partial order relationship between the rows in the Boolean lattice structure, the first row of Booleans can be directly used as the maximum element, and the last row of Booleans can be directly used as the minimum element. That is, the maximum element and the minimum element can be directly determined according to the result of each division, without the need to further calculate the number of failed component states of each system state under the Boolean lattice structure after each division to determine the maximum element and the minimum element from the system state after counting the number of failed component states, thereby further improving the recognition efficiency of the maximum element and the minimum element, which is simpler and more convenient.

[0050] The Boolean structure is generated by arranging different rows in descending order of order, and then the Boolean structure is divided by binary search. The two Boolean substructures obtained by each division contain the same number of system states, and the first row of each Boolean substructure includes one system state, and the last row includes one system state. This division method is used to calculate the reliability of the power system to be analyzed, and the calculation results are compared with those of the enumeration method and the Monte Carlo simulation method. The comparison results are shown in Table 1.

[0051] Table 1. Results comparison 1

[0052]

[0053] For the same power system to be analyzed, Table 1 shows the corresponding effects of different reliability analysis methods. Generally speaking, the enumeration method analyzes the power system operating state corresponding to each system state, so the accuracy of its reliability is relatively high, and the reliability of the power system can be expressed using LOLP (Loss Of Load Probability, load loss probability). As can be seen from Table 1, the dichotomy based on Boolean structure division proposed in this application is compared with the enumeration method and the Monte Carlo simulation method in identifying the system state that makes the operating state of the power system to be analyzed in the failed system state from the system state space. The number of evaluations and the time required for analysis are greatly reduced. In addition, the calculation results of LOLP are very close to the LOLP calculation results of the enumeration method, indicating that the accuracy of the reliability calculated by the dichotomy method of this application is also relatively high.

[0054] In addition, when the number of evaluations corresponding to the enumeration method and the binary method of the present application is fixed, for almost the same analysis time, the results of the analysis can be seen in Table 2.

[0055] Table 2. Results comparison 2

[0056]

[0057] For the same power system to be analyzed, Table 2 shows the comparison of results corresponding to different reliability analysis methods. In Table 2, Ng represents the number of system states that have been evaluated to make the power system in a normal system state, Nr represents the number of system states that have been evaluated to make the power system in a failed system state, and Ny represents the number of all system states that have been evaluated. Using the binary search method, 26,332 evaluations are performed to complete the screening of critical system states. It can be seen from Table 2 that for the same number of evaluations, the number of system states that can be identified by the binary search method is much larger than the enumeration method, from which it can be seen that the efficiency of the binary search method in this application is high.

[0058] Step 204, according to the power system operating states corresponding to the maximum element and the minimum element, determine to continue dividing the Boolean lattice structure or put it into the corresponding target system state space until a preset division condition is met, wherein the target system state space includes a normal system state space and a failure system state space.

[0059] Step 205: take the system state contained in the failure system state space as the target system state; obtain the failure probability corresponding to each component in the power system to be analyzed, and calculate the first occurrence probability corresponding to each target system state based on the failure probability; sum the first occurrence probabilities corresponding to the target system states to obtain the second occurrence probability, and determine the reliability corresponding to the power system to be analyzed according to the second occurrence probability.

[0060] In this embodiment, the system state in the failed system state space can be used as the target system state. For example, if the failed system state includes 20 system states, then these 20 system states are used as the target system state. Further, the failure probability of each component in the power system to be analyzed can be obtained, and the first occurrence probability corresponding to each target system state can be calculated using these failure probabilities. Assuming that the power system to be analyzed contains 5 components, and the failure probabilities of these 5 components are p1, p2, ..., p5, then for a certain target system state s, such as (1, 0, 1, 0, 1), its probability of occurrence (that is, the first occurrence probability) is p(s) = p1*(1-p2)*p3*(1-p4)*p5. After calculating the first occurrence probability corresponding to each target system state, these first occurrence probabilities can be summed to obtain the second occurrence probability. Based on these results, the reliability of the power system to be analyzed can be calculated.

[0061] Step 206, determining the relationship between the reliability of the power system to be analyzed and a preset reliability threshold, and when the determination result indicates that the reliability value is less than the preset reliability threshold, generating an alarm message, and sending the alarm message to a preset processing terminal.

[0062] In this embodiment, a reliability threshold can be set in advance. When the calculated reliability of the power system to be analyzed is less than the preset reliability threshold, it means that the current operating state of the power system to be analyzed may be risky or unstable, and an alarm message can be generated at this time. This alarm message may include the calculated reliability assessment result of the power system to be analyzed, the degree of being lower than the preset reliability threshold, the judgment time and other information. Afterwards, the generated alarm message can be sent to a preset processing terminal. Here, the preset processing terminal can be a computer, mobile device, mail system, etc. responsible for monitoring the power system to ensure that relevant personnel can receive the alarm in time and make a response strategy.

[0063] In an embodiment of the present application, optionally, the step 204 of "determining whether to continue dividing the Boolean lattice structure or placing it into the corresponding target system state space according to the power system operating states corresponding to the maximum element and the minimum element" includes: when the power system operating states corresponding to the maximum element and the minimum element are both normal system states, placing the Boolean lattice structure into the normal system state space; when the power system operating state corresponding to the maximum element is a failure system state, and the power system operating state corresponding to the minimum element is a normal system state, determining the Boolean lattice structure as a Boolean lattice structure to be divided, and returning to the step of dividing the Boolean lattice structure into two Boolean lattice structures based on the dichotomy method; when the power system operating states corresponding to the maximum element and the minimum element are both failure system states, placing the Boolean lattice structure into the failure system state space.

[0064] In this embodiment, if the power system operating state corresponding to the maximum element and the power system operating state corresponding to the minimum element are both normal system states, then since the Boolean lattice structure also satisfies the partial order relationship, it means that the system states in the Boolean lattice structure are all system states that make the power system to be analyzed in a normal system state. At this time, the system states contained in the Boolean lattice structure can be placed in the normal system state space.

[0065] If the operating state of the power system corresponding to the maximum element is a failed system state, but the operating state of the power system corresponding to the minimum element is a normal system state, then at this time, it cannot be directly judged whether the various system states in the Boolean lattice structure make the power system to be analyzed in a normal system state or in a failed system state. Therefore, the Boolean lattice structure can be used as a new Boolean structure to be divided, and the new Boolean structure to be divided can be divided again using the dichotomy method, and the above judgment can be repeated.

[0066] If the power system operating states corresponding to the maximum element and the minimum element are both failed system states, then it means that the system states in the Boolean lattice structure are all system states that make the power system to be analyzed in a failed system state. At this time, the system states contained in the Boolean lattice structure can be placed in the failed system state space.

[0067] After multiple divisions, the process ends when the preset division conditions are finally met, indicating that all division work has been completed. The failure system state space at this time is the failure system state space that is ultimately used to calculate the reliability of the power system to be analyzed.

[0068] In an embodiment of the present application, optionally, the method further includes: when the power system operating states corresponding to the maximum element and the minimum element are both normal system states, placing the maximum element in a normal critical system state space; when the power system operating states corresponding to the maximum element and the minimum element are both failure system states, placing the minimum element in a failure critical system state space.

[0069] In this embodiment, while adding the Boolean lattice structure to the normal system state space and the failure system state space, a normal critical system state space and a failure critical system state space can also be set, the normal critical system state space can be used to add a critical system state that makes the power system to be analyzed in a normal system state, and the failure critical system state space can be used to add a critical system state that makes the power system to be analyzed in a failure system state. Specifically, when determining the power system operation state corresponding to the maximum element and the minimum element in each Boolean lattice structure, if it is found that the power system operation state corresponding to the maximum element and the minimum element is a normal system state, then the maximum element belongs to the critical system state that makes the power system to be analyzed in a normal system state, and the maximum element can be placed in the normal critical system state space; similarly, if the power system operation state corresponding to the maximum element and the minimum element is a failure system state, then the minimum element belongs to the critical system state that makes the power system to be analyzed in a failure system state, and the minimum element can be placed in the failure critical system state space. That is to say, after the present application determines the operating state of the power system corresponding to the maximum element and the minimum element, in addition to adding the qualified Boolean lattice substructure to the normal system state space and the failure system state space, the qualified maximum element and minimum element can also be added to the normal critical system state space and the failure critical system state space, so that when the preset division conditions are met, the critical system state is also identified. The whole process does not require any other additional calculations, that is, the Boolean is divided according to multiple attributes, which is simple and convenient. When you want to determine the critical system state of the power system to be analyzed later, you only need to find the critical system state from the normal critical system state space and the failure critical system state space, and you can directly analyze it.

[0070] In an embodiment of the present application, optionally, the method further includes: recording the number of divisions of the Boolean lattice structure, and determining that a preset division condition is met when the number of divisions reaches a preset number threshold; and / or, after placing the Boolean lattice substructure into the corresponding target system state space, calculating a first total number of system states contained in the normal system state space and the failure system state space, and calculating a ratio between the first total number and the second total number, and when the ratio reaches a preset ratio threshold, determining that the preset division condition is met, wherein the second total number is the total number of system states in the system state space; and / or, after placing the Boolean lattice substructure into the corresponding target system state space, calculating a first total number of system states contained in the normal system state space and the failure system state space, and when the first total number is consistent with the second total number, determining that the preset division condition is met.

[0071] In this embodiment, whether the preset division condition is met can be determined in the following ways:

[0072] The first is that when dividing the Boolean structure, the number of binary divisions can be recorded. When the number of divisions reaches the preset number threshold, it is determined that the preset division condition is met and the whole process ends. Here, the preset number threshold can be determined according to demand. When the Boolean structure contains fewer system states, the preset number threshold can be (f-1) times, where f represents the number of system states in the system state space; when the Boolean structure contains more system states, the preset number threshold can be a value set according to experience and less than f. This value can not only ensure the basic accuracy of the reliability calculation of the power system to be analyzed, but also avoid excessive division times, which causes unnecessary waste of computing resources.

[0073] The second method is that each time a new Boolean lattice structure is added to the corresponding target system state space, the number of system states in the normal system state space and the number of system states in the failed system state space can be calculated, and the two numbers are added together to obtain the first total number of system states that have been divided. Then the ratio between the first total number and the second total number is calculated. If the ratio reaches the preset ratio threshold, it means that the preset division condition has been met, and the whole process can be judged to be over. The failed system state space at this time is the failed system state space that is ultimately required. Here, the number of all system states contained in the system state space of the power system to be analyzed is the above-mentioned second total number.

[0074] The third method is that each time a new Boolean lattice structure is added to the corresponding target system state space, the number of system states in the normal system state space and the number of system states in the failed system state space can be calculated, and the two numbers are added together to obtain the first total number of system states that have been divided. Then the first total number is compared with the second total number. If the first total number is equal to the second total number, it means that all system states have either been added to the normal system state space or to the failed system state space. It can be judged that the whole process is over, and the failed system state space at this time is the failed system state space that is finally required.

[0075] In addition, it is also possible to determine whether the preset division conditions are met by presetting a reliability threshold. For example, the reliability threshold of the power system to be analyzed is pre-set to 60%, that is, as long as it is greater than 60%, the requirement is met. Then, each time the Boolean lattice structure is added to the corresponding target system state space, the reliability of the power system to be analyzed is calculated once. When the calculation finds that the reliability of the power system to be analyzed has reached 60%, it can be determined that the preset division conditions are met, and the remaining Boolean lattice structures are stopped from being further divided, and the whole process ends.

[0076] The embodiments of the present application determine whether the preset partitioning condition is met in different ways, so that the determination of the termination condition of the Boolean structure partitioning can be more flexible and can meet different partitioning requirements.

[0077] The embodiment of the present application also provides a computer device, which can be a personal computer, a server, a network device, etc. The computer device includes a bus, a processor, a memory and a communication interface, and can also include an input and output interface and a display device. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store location information. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, the steps in each method embodiment are implemented.

[0078] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties.

[0079] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited to this.

[0080] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0081] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A power system reliability assessment method based on Boolean partitioning, characterized in that: include: Arrange and combine the component state of each component in the power system to be analyzed to obtain multiple component state combinations, and use each component state combination as a system state to construct a system state space of the power system to be analyzed, wherein each system state includes an component state of each component, and the component state is a normal component state or a failed component state; Defining a partial order relationship between each system state in the system state space, and constructing a Boolean structure corresponding to the power system to be analyzed according to the partial order relationship; Dividing the Boolean lattice structure into two Boolean lattice substructures based on the dichotomy method, determining the maximum element and the minimum element in each Boolean lattice structure respectively, and determining whether to continue dividing the Boolean lattice structure or put it into the corresponding target system state space according to the power system operation state corresponding to the maximum element and the minimum element until a preset division condition is met, wherein the target system state space includes a normal system state space and a failure system state space; The target system state is determined through the failed system state space, and the reliability of the power system to be analyzed is evaluated based on the target system state.

2. The method according to claim 1, characterized in that The method of defining a partial order relationship between each system state in the system state space and constructing a Boolean structure corresponding to the power system to be analyzed according to the partial order relationship includes: Dividing the system states in the system state space according to the order to obtain system state spaces of each order, wherein the number of failed component states contained in each system state in each order system state space is the same; Arrange the system states contained in each order system state space into a row, and arrange the rows in descending order of order to obtain a Boolean structure corresponding to the power system to be analyzed; Accordingly, the method of dividing the Boolean lattice structure into two Boolean lattice substructures based on the dichotomy method and determining the maximum element and the minimum element in each Boolean lattice substructure respectively includes: Dividing the Boolean structure based on a dichotomy method to obtain two Boolean substructures, wherein the two Boolean substructures contain the same number of system states, and the first row and the last row of each Boolean substructure respectively include one system state; The system status of the first row is used as the maximum element, and the system status of the last row is used as the minimum element.

3. The method according to claim 1, characterized in that Before dividing the Boolean structure into two Boolean substructures based on the dichotomy method, the method further includes: Obtaining a system structure diagram and system parameters corresponding to the power system to be analyzed; Based on the system structure diagram and the system parameters, construct a target DC power flow equation and an optimal load shedding model of the power system to be analyzed; Accordingly, after respectively determining the maximum element and the minimum element in each Boolean lattice structure, the method further includes: Solving a first load shedding amount of an optimal load shedding model constrained by the target DC power flow equation according to the system state corresponding to the maximum element, and determining the power system operation state corresponding to the maximum element according to the first load shedding amount; and According to the system state corresponding to the minimum element, a second load shedding amount of the optimal load shedding model with the target DC power flow equation as a constraint is solved, and according to the second load shedding amount, the power system operation state corresponding to the minimum element is determined.

4. The method according to claim 1, characterized in that: The step of determining, according to the power system operation states corresponding to the maximum element and the minimum element, to continue dividing the Boolean lattice structure or placing it into the corresponding target system state space comprises: When the power system operation states corresponding to the maximum element and the minimum element are both normal system states, placing the Boolean lattice structure into a normal system state space; When the power system operation state corresponding to the maximum element is a failed system state, and the power system operation state corresponding to the minimum element is a normal system state, the Boolean lattice structure is determined as a Boolean lattice structure to be divided, and the method returns to the step of dividing the Boolean lattice structure into two Boolean lattice structures based on the dichotomy method; When the power system operation states corresponding to the maximum element and the minimum element are both failure system states, the Boolean lattice structure is placed in the failure system state space.

5. The method according to claim 4, characterized in that The method further comprises: When the power system operation states corresponding to the maximum element and the minimum element are both normal system states, placing the maximum element into a normal critical system state space; When the power system operating states corresponding to the maximum element and the minimum element are both failure system states, the minimum element is placed in the failure critical system state space.

6. The method according to any one of claims 2 to 5, characterized in that The method further comprises: Recording the number of divisions of the Boolean structure, and when the number of divisions reaches a preset number threshold, determining that a preset division condition is satisfied; and / or, After placing the Boolean lattice structure into the corresponding target system state space, calculating a first total number of system states contained in the normal system state space and the failed system state space, and calculating a ratio between the first total number and a second total number, and when the ratio reaches a preset ratio threshold, determining that a preset division condition is met, wherein the second total number is the total number of system states in the system state space; and / or, After placing the Boolean lattice structure into the corresponding target system state space, a first total number of system states contained in the normal system state space and the failed system state space is calculated, and when the first total number is consistent with the second total number, it is determined that the preset division condition is met.

7. The method according to claim 1, characterized in that Determining the target system state through the failed system state space, and evaluating the reliability of the power system to be analyzed according to the target system state, includes: Taking the system state contained in the failed system state space as the target system state; Obtaining a failure probability corresponding to each component in the power system to be analyzed, and calculating a first occurrence probability corresponding to each target system state based on the failure probability; The first occurrence probabilities corresponding to the target system states are summed to obtain a second occurrence probability, and the reliability corresponding to the power system to be analyzed is determined according to the second occurrence probability.

8. The method according to claim 7, characterized in that After determining the reliability corresponding to the power system to be analyzed according to the second occurrence probability, the method further includes: The relationship between the reliability corresponding to the power system to be analyzed and a preset reliability threshold is determined, and when the determination result indicates that the reliability value is less than the preset reliability threshold, an alarm message is generated and sent to a preset processing terminal.

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