Power distribution network multi-level cluster planning method and system considering power supply reliability

Abstract

The invention discloses a power distribution network multi-level cluster planning method and system considering power supply reliability, and the method comprises the steps: obtaining power distribution network data, carrying out the initial cluster division, and building a multi-level planning model which comprises a cluster line planning layer, a source-storage addressing and sizing layer and a reliability index calculation layer; solving a cluster line planning layer objective function to obtain a line planning scheme; solving a source-storage addressing and sizing layer objective function to obtain a source-storage addressing and sizing scheme; and according to the line planning scheme and the source-storage addressing and sizing scheme, reliability index calculation is carried out, a reliability index calculation result is returned to a source-storage addressing and sizing layer and a cluster line planning layer, and the multi-level planning model iterates to obtain an optimal cluster division scheme. Through the innovative cluster reliability index calculation method, the complexity of reliability evaluation of a large-scale system is simplified, and the efficiency and accuracy of reliability evaluation are improved; the complexity of the optimization process is reduced, and the optimization time is shortened.

Description

Technical Field

[0001] The present invention relates to the technical field of distribution network planning, and in particular to a distribution network multi-level cluster planning method and system considering power supply reliability. Background Art

[0002] The simulation method has been widely used in the calculation of reliability indicators of distribution networks containing distributed power sources. However, this method requires the analysis of the parameters of all components in the distribution network. The process is relatively complicated, the amount of calculation is large, and the efficiency is not high. Regardless of the simulation method or the analytical method, the calculation of reliability indicators is usually based on a fixed network and distributed power access. However, when planning the distribution network, the topology of the distribution network and the access of distributed power sources are often uncertain, and there is uncertainty. When calculating the reliability indicators under uncertain conditions, not only does the calculation result not meet the actual requirements of the distribution network planning scheme, but there may also be unsolvable situations. In order to solve this challenge, some researchers decompose the distribution network planning model and the reliability index, and then solve them separately, and finally summarize the results. However, this approach may lead to inaccuracy in the calculation, and thus the optimal planning scheme cannot be obtained. In order to avoid the problems caused by decomposition calculations, some researchers have proposed to solve the distribution network planning model and the reliability index expression simultaneously. Unfortunately, this method makes it difficult to obtain the results.

[0003] Considering the reliability of power supply on the basis of economic planning of distribution network, the reliability index of power supply is often calculated when the grid structure of distribution network is determined, the location and capacity of distributed renewable energy access are determined. However, for the distribution network to be planned, the distributed renewable energy and grid structure are uncertain, and considering the volatility of distributed renewable energy power output and load demand power, it is necessary to further study the calculation of reliability index to ensure the effectiveness of distribution network planning scheme on the basis of considering reliability index. Based on this, in order to ensure that the distribution network can still operate economically and reliably under the uncertainty of renewable energy and load power, it is necessary to carry out iterative dynamic calculation of distribution network planning, that is, the close coupling of reliability and economy based on the dynamic division of clusters. Summary of the invention

[0004] The purpose of this section is to summarize some aspects of embodiments of the present invention and briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section and the specification abstract and the invention title of this application to avoid blurring the purpose of this section, the specification abstract and the invention title, and such simplifications or omissions cannot be used to limit the scope of the present invention.

[0005] In view of the above existing problems, the present invention is proposed. Therefore, the present invention provides a distribution network multi-level cluster planning method considering power supply reliability to solve the problems of complex calculation, cumbersome optimization process and inaccurate results in the distribution network planning process under the condition of distributed power supply and load power uncertainty.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0007] In a first aspect, the present invention provides a distribution network multi-level cluster planning method considering power supply reliability, comprising:

[0008] Acquire distribution network data, perform initial cluster division according to the distribution network data and establish a multi-level planning model, wherein the multi-level planning model includes a cluster line planning layer, a source-storage addressing and capacity determination layer, and a reliability index calculation layer;

[0009] Based on the photovoltaic and load forecast values ​​of the distribution network, with the goal of minimizing the line planning cost and network loss cost, a cluster line planning layer objective function is established, and the cluster line planning layer objective function is solved to obtain a line planning solution;

[0010] Based on the line planning scheme, with the goal of minimizing the annual investment and operation and maintenance costs of photovoltaics, the annual income of photovoltaics, and the annual investment cost of energy storage, a source-storage addressing and capacity-fixing layer objective function is established, and the source-storage addressing and capacity-fixing layer objective function is solved to obtain the source-storage addressing and capacity-fixing scheme;

[0011] The reliability index calculation layer calculates the reliability index according to the line planning scheme and the source-reservoir addressing and sizing scheme, and returns the reliability index calculation result to the source-reservoir addressing and sizing layer and the cluster line planning layer. The cluster line planning layer, the source-reservoir addressing and sizing layer and the reliability index calculation layer repeatedly iterate to obtain the optimal cluster division scheme.

[0012] As a preferred solution of the multi-level cluster planning method for distribution network considering power supply reliability described in the present invention, the objective function of the cluster line planning layer includes:

[0013] Based on the initial cluster division results and the photovoltaic and load forecast values, the distribution network line is expanded and planned with the goal of minimizing the line planning cost and network loss cost, and the cluster line planning layer objective function is established. The cluster line planning layer objective function is expressed as:

[0014] minf=F1+F2

[0015]

[0016] Among them, F1 is the annual investment cost of the network, F2 is the network power transmission loss cost, Ω sis the set of nodes in the branch network, is the set of child nodes of node i, C l Indicates the investment cost per kilometer of the line, D ij refers to the length of the line between nodes i and j, x ij is a 0-1 variable for the line between nodes i and j, where 1 indicates that the line has been installed, 0 indicates that the line has not been installed, χ indicates the bank interest rate, β indicates the investment payback period, and C e represents the electricity price, N n,k Indicates the number of nodes contained in cluster k, i ij,t represents the square value of the current in the line between nodes i and j at time t, ε ij Represents the line resistance value between nodes i and j.

[0017] As a preferred solution of the multi-level cluster planning method for distribution network considering power supply reliability described in the present invention, wherein: establishing the source-storage addressing and capacity-fixed layer objective function includes:

[0018] Based on the line planning scheme and combined with the uncertainty of photovoltaic and load, the investment and operation and maintenance costs of the source-storage in the cluster are minimized, and the source-storage addressing and capacity-fixed layer objective function is established. The source-storage addressing and capacity-fixed layer objective function is expressed as:

[0019] minF=F3-F4+F5

[0020]

[0021] Among them, F3 is the annual investment and operation and maintenance cost of photovoltaic in cluster k, F4 is the annual income of photovoltaic in cluster k, F5 is the annual investment cost of energy storage in cluster k, and C PV is the investment cost per MW of photovoltaic power, C OMPV is the annual fixed maintenance cost per MW PV, П k is the set of nodes contained in cluster k, S PV,j is the original planned PV capacity of node j in cluster k, S PVf,j is the planned PV capacity added to node j in cluster k, C sell and C sub are the grid-connected electricity price and subsidized electricity price of distributed power sources, ω PV,t is the maximum output of photovoltaic power per megawatt under given sunshine conditions at time t, ρ is the discount rate, r is the number of years of discount, c bat is the investment cost per unit capacity of energy storage, P batt,j Configure the energy storage capacity for node j.

[0022] As a preferred solution of the multi-level cluster planning method for distribution network considering power supply reliability described in the present invention, the uncertainty of photovoltaic and load includes:

[0023] The box-type uncertainty set is used to obtain the uncertainty range of active load power, reactive load power and photovoltaic output, and the uncertainty parameters are introduced to regulate the configuration strategy of the source-storage addressing and sizing scheme.

[0024] As a preferred solution of the multi-level cluster planning method for distribution network considering power supply reliability described in the present invention, the reliability index calculation includes:

[0025] Calculating a reliability index according to the line planning scheme and the source-storage addressing and sizing scheme, wherein the reliability index is the power outage loss cost for the user;

[0026] The objective function of the reliability index calculation layer is established with the goal of minimizing the power outage loss cost of users. The objective function of the reliability index calculation layer is expressed as:

[0027]

[0028] Among them, ECOST is the power outage loss cost for users in cluster k, λ j is the failure rate of the jth node, i.e., the average number of power outages, r j is the average power outage time of the jth node failure, is the average load value of node j, N n,l is the total number of nodes connecting branches in cluster k, H j is the loss cost caused by power outage of the average load of node j, is the maximum interruption time of the average load of node j, is the maximum interruption of the average load of node j.

[0029] As a preferred solution of the multi-level cluster planning method for distribution network considering power supply reliability described in the present invention, it also includes:

[0030] Based on the probability of cluster island operation, the node failure rate and average power outage time of different types of cluster tie switches are calculated using the minimum path method and breadth-first search method.

[0031] The reliability index is calculated according to the node failure rate and the average power outage time of the node failure of the different types of cluster tie switches in combination with the reliability index calculation layer constraints.

[0032] As a preferred solution of the multi-level cluster planning method for distribution network considering power supply reliability described in the present invention, the reliability index calculation layer constraints include:

[0033] The constraints of the reliability index calculation layer include the maximum interruption time of the average node load and the maximum interruption amount of the average node load. The node load interruption time and the average node load interruption amount must meet the following requirements:

[0034]

[0035] in, is the upper limit of the maximum interruption of the average load of node j, is the upper limit of the maximum interruption time of the average load of node j, is the average load interruption time of node j.

[0036] In a second aspect, the present invention provides a system for multi-level cluster planning of a distribution network considering power supply reliability, comprising:

[0037] A multi-level model building module, used to build a multi-level planning model, wherein the multi-level planning model includes a cluster line planning layer, a source-reservoir addressing and capacity determination layer, and a reliability index calculation layer;

[0038] The cluster line planning module is used to establish a cluster line planning layer objective function based on the distribution network photovoltaic and load forecast values, with the goal of minimizing line planning cost and network loss cost, and solve the cluster line planning layer objective function to obtain a line planning solution;

[0039] A source-storage addressing and capacity determination module is used to establish a source-storage addressing and capacity determination layer objective function based on the line planning scheme, with the goal of minimizing the annual investment and operation and maintenance costs of photovoltaics, the annual income of photovoltaics, and the annual investment cost of energy storage, and solve the source-storage addressing and capacity determination layer objective function to obtain a source-storage addressing and capacity determination scheme;

[0040] A reliability index calculation module, used for the reliability index calculation layer to calculate the reliability index according to the line planning scheme and the source-storage addressing and capacity determination scheme;

[0041] The optimal cluster partitioning scheme acquisition module is used to return the reliability index calculation results to the source-reservoir addressing and capacity determination layer and the cluster line planning layer. The cluster line planning layer, the source-reservoir addressing and capacity determination layer and the reliability index calculation layer repeatedly iterate to obtain the optimal cluster partitioning scheme.

[0042] In a third aspect, the present invention provides a computing device, comprising:

[0043] Memory and processor;

[0044] The memory is used to store computer executable instructions, and the processor is used to execute the computer executable instructions. When the computer executable instructions are executed by the processor, the steps of the distribution network multi-level cluster planning method considering power supply reliability are implemented.

[0045] In a fourth aspect, the present invention provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the steps of the distribution network multi-level cluster planning method considering power supply reliability.

[0046] Compared with the prior art, the present invention has the following beneficial effects: the present invention significantly simplifies the complexity of large-scale system reliability evaluation through an innovative cluster reliability index calculation method, so that cluster-based reliability indicators can be directly obtained after cluster division, thereby effectively improving the efficiency and accuracy of reliability evaluation; under the premise of fully considering the reliability index, the complexity of the optimization process is greatly reduced, the demand for computing resources of the variable dimension is reduced, and the optimization time is greatly shortened, providing an efficient and feasible solution for reliability optimization of complex systems. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] 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 labor. Among them:

[0048] Figure 1 It is a schematic diagram of the overall process of a multi-level cluster planning method for a distribution network considering power supply reliability according to an embodiment of the present invention;

[0049] Figure 2 A schematic diagram of simple distribution network cluster division of a distribution network multi-level cluster planning method considering power supply reliability according to an embodiment of the present invention;

[0050] Figure 3 A schematic diagram of a reliability index calculation process of a distribution network multi-level cluster planning method considering power supply reliability according to an embodiment of the present invention;

[0051] Figure 4 A schematic diagram of a three-layer planning solution process based on cluster division of a multi-level cluster planning method for a distribution network considering power supply reliability according to an embodiment of the present invention;

[0052] Figure 5 A schematic diagram of geographical connection of a power distribution network according to a method for planning a multi-level cluster of a power distribution network taking into account power supply reliability according to an embodiment of the present invention;

[0053] Figure 6 A schematic diagram of photovoltaic planning capacity of different schemes of a multi-level cluster planning method for a distribution network considering power supply reliability according to an embodiment of the present invention;

[0054] Figure 7 A schematic diagram of energy storage access capacity under different schemes of a multi-level cluster planning method for a distribution network considering power supply reliability according to an embodiment of the present invention;

[0055] Figure 8 A schematic diagram of average power outage times of a distribution network multi-level cluster planning method considering power supply reliability according to an embodiment of the present invention;

[0056] Fig. 9 A schematic diagram of average power outage time of a distribution network multi-level cluster planning method considering power supply reliability according to an embodiment of the present invention. DETAILED DESCRIPTION

[0057] In order to make the above-mentioned purposes, 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 drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0058] 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.

[0059] 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.

[0060] The present invention is described in detail with reference to schematic diagrams. When describing the embodiments of the present invention, for the sake of convenience, the cross-sectional diagrams showing the device structure will not be partially enlarged according to the general scale, and the schematic diagrams are only examples, which should not limit the scope of protection of the present invention. In addition, in actual production, the three-dimensional dimensions of length, width and depth should be included.

[0061] At the same time, in the description of the present invention, it should be noted that the orientations or positional relationships indicated by the terms "upper, lower, inner and outer" are based on the orientations or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the system or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, the terms "first, second or third" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0062] In the present invention, unless otherwise clearly specified and limited, the terms "install, connect, connect" should be understood in a broad sense, for example: it can be a fixed connection, a detachable connection or an integral connection; it can also be a mechanical connection, an electrical connection or a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0063] Example 1

[0064] Reference Figure 1-4 , which is an embodiment of the present invention, provides a distribution network multi-level cluster planning method considering power supply reliability, comprising:

[0065] S100: Obtain distribution network data, perform initial cluster division according to the distribution network data and establish a multi-level planning model, the multi-level planning model includes a cluster line planning layer, a source-storage addressing and capacity determination layer and a reliability index calculation layer;

[0066] Specifically, the distribution network data includes network topology, load data (including historical, current and predicted values), photovoltaic resource data, energy storage system data, equipment parameters, etc.; the distribution network data is preprocessed, including data cleaning, sorting and verification, to ensure the accuracy and completeness of the data; then, the cluster analysis method is used to preliminarily divide the equipment in the distribution network;

[0067] In a possible embodiment, during the clustering process, factors such as the geographical location of the equipment, load characteristics, and power supply reliability requirements are comprehensively considered, and a suitable clustering algorithm, such as K-means, hierarchical clustering, etc., is selected for calculation.

[0068] S102: Based on the photovoltaic and load forecast values ​​of the distribution network, with the goal of minimizing the line planning cost and network loss cost, establish a cluster line planning layer objective function, and solve the cluster line planning layer objective function to obtain a line planning solution;

[0069] It should be noted that the photovoltaic and load forecast values ​​are known numbers in the present invention and can be obtained by the forecasting software;

[0070] Preferably, based on the initial cluster division results and the photovoltaic and load forecast values, the distribution network line is expanded and planned with the goal of minimizing the line planning cost and network loss cost, and a cluster line planning layer objective function is established. The cluster line planning layer objective function is expressed as:

[0071] minf=F1+F2

[0072]

[0073] Among them, F1 is the annual investment cost of the network, F2 is the network power transmission loss cost, Ω s is the set of nodes in the branch network, is the set of child nodes of node i, C l Indicates the investment cost per kilometer of the line, D ij refers to the length of the line between nodes i and j, x ij is a 0-1 variable for the line between nodes i and j, where 1 indicates that the line has been installed, 0 indicates that the line has not been installed, χ indicates the bank interest rate, β indicates the investment payback period, and C e represents the electricity price, N n,k Indicates the number of nodes contained in cluster k, i ij,t represents the square value of the current in the line between nodes i and j at time t, ε ij represents the line resistance value between nodes i and j;

[0074] In the embodiment of the present application, when solving the objective function of the cluster line planning layer to obtain the line planning solution, the power balance constraint and the voltage and current constraint should be observed. The power balance constraint and the voltage and current constraint are expressed as:

[0075]

[0076] 0≤v′ i,t ≤Wx ij

[0077] -W(1-x ij )+ν i,t ≤ν′ i,t ≤ν i,t

[0078] ||2P ij,t 2Q ij,t i ij,t -ν i,t ||2≤i ij,t +v i,t

[0079] x ij v min ≤v i,t ≤x ij vmax

[0080]

[0081] The upstream node set of node j is defined as ψ j , the reactance of the line between nodes i and j is expressed as δ ij At time t, the active and reactive power flowing through the line between nodes i and j are denoted as P ij,t and Q ij,t The efficiency of energy storage charging and discharging is represented by η, and the energy storage charging power and discharging power of node j at time t are represented by P CH,j, and P DS,j,t It means that at time t, the active and reactive loads of node j are represented as P L,j,t and Q L,j,t , P PV,j,t represents the actual active power generation of the photovoltaic (PV) at node j at time t. If the PV of node j needs to increase its active power generation at time t, it is recorded as P PVf,j,t , the downstream node set of node j is It means that at time t, the actual reactive power generated by the PV of node j is Q PV,j,t If the PV of node j needs to increase reactive power at time t, it is recorded as Q PVf,j,t , v i,t It represents the square of the voltage value of node i at time t, through the line variable x ij Constrain the voltage square of the node i to which it is connected, using v' i,t Indicates that W represents a sufficiently large constant, v min and v max They represent the lower and upper limits of voltage respectively, and the maximum limit of current is I max express;

[0082] It should be noted that the present invention establishes an objective function for the cluster line planning layer by comprehensively considering the photovoltaic and load forecast values ​​of the distribution network, with the goal of minimizing the line planning cost and network loss cost. The objective function not only takes into account the economic efficiency of the line investment, but also incorporates the cost of network power transmission loss, thereby ensuring that the economy and technical feasibility can be balanced during the planning process; by introducing power balance constraints and voltage and current constraints, the stability and safety of the planning scheme in actual operation are ensured, the construction and operation costs of the distribution network are effectively reduced, and the power supply reliability and efficiency of the system are improved.

[0083] S104: Based on the line planning scheme, with the goal of minimizing the annual investment and operation and maintenance costs of photovoltaics, the annual income of photovoltaics, and the annual investment cost of energy storage, a source-storage addressing and capacity-fixing layer objective function is established, and the source-storage addressing and capacity-fixing layer objective function is solved to obtain a source-storage addressing and capacity-fixing scheme;

[0084] Preferably, based on the line planning scheme and combined with the uncertainty of photovoltaic and load, the investment and operation and maintenance costs of the source-storage in the cluster are minimized, and the source-storage addressing and capacity-fixed layer objective function is established. The source-storage addressing and capacity-fixed layer objective function is expressed as:

[0085] minF=F3-F4+F5

[0086]

[0087] Among them, F3 is the annual investment and operation and maintenance cost of photovoltaic in cluster k, F4 is the annual income of photovoltaic in cluster k, F5 is the annual investment cost of energy storage in cluster k, and C PV is the investment cost per MW of photovoltaic power, C OMPV is the annual fixed maintenance cost per MW PV, П k is the set of nodes contained in cluster k, S PV,j is the original planned PV capacity of node j in cluster k, S PVf,j is the planned PV capacity added to node j in cluster k, C sell and C sub are the grid-connected electricity price and subsidized electricity price of distributed power sources, ω PV,t is the maximum output of photovoltaic power per megawatt under given sunshine conditions at time t, ρ is the discount rate, r is the number of years of discount, c bat is the investment cost per unit capacity of energy storage, P batt,j Configure the energy storage capacity for node j;

[0088] Preferably, a box-type uncertainty set is used to obtain the uncertainty range of active load power, reactive load power and photovoltaic output, and an uncertainty parameter is introduced to regulate the configuration strategy of the source-storage addressing and sizing scheme;

[0089] Specifically, since active load, reactive load and photovoltaic output are uncertain, simply predicting their specific values ​​is often accompanied by large errors, resulting in the source-storage addressing and sizing scheme being not the optimal solution. Therefore, the present invention adopts a box-type uncertainty set to describe the uncertainty range of active load power, reactive load power and photovoltaic output, and introduces uncertainty parameters to adjust the conservative degree of the optimal solution. The larger the value of the uncertainty parameter, the more conservative the source-storage addressing and sizing scheme is; otherwise, the more radical the source-storage addressing and sizing scheme is. The photovoltaic and load uncertainty constraints are expressed as:

[0090]

[0091] Among them, U represents the box-type uncertain set, P L,j,t , Q L,j,t and P PV,j,t are the uncertain variables of active load power, reactive load power and photovoltaic output of node j in cluster k, and are the predicted values ​​of active load power, reactive load power and photovoltaic output of node j in cluster k, ΔP L,j,t , ΔQ L,j,t and ΔP PV,j,t are the fluctuation deviations of active load power, reactive load power and photovoltaic output of node j in cluster k, N a 、N b 、N e are the total number of active load nodes, the total number of reactive load nodes, and the total number of photovoltaic nodes, respectively. PL , Γ QL and Γ PV are the uncertain adjustment parameters introduced by active load power, reactive load power and photovoltaic output, and their value ranges are 0 to N respectively. a , 0 to N b and 0 to N e integer;

[0092] In the embodiment of the present application, when solving the source-storage addressing and sizing layer objective function to obtain the source-storage addressing and sizing solution, in addition to satisfying the photovoltaic and load uncertainty constraints, it is also necessary to satisfy the energy storage constraint, the power balance constraint and the voltage and current constraint. Specifically, the energy storage constraint is expressed as:

[0093]

[0094] soc min P batt,j ≤soc j,t ≤soc max P batt,j ,j∈Πk k ,t∈T k,ESS

[0095]

[0096] The state of charge of the energy storage of node j in cluster k at time t is represented as soc j,t , sets the minimum state of charge soc for energy storage min and maximum state of charge soc max , P CH,max is the maximum charging power of energy storage, P DS,max is the maximum discharge power of energy storage;

[0097] It should be noted that the maximum energy storage configuration capacity within the simulated operation time of the energy storage is taken as the energy storage installation capacity of each cluster. The power balance constraint and the voltage and current constraint have been explained in S102 and will not be explained in detail here.

[0098] It should also be noted that the present invention establishes a source-storage addressing and capacity-fixed layer objective function by comprehensively considering the uncertainties of photovoltaics and loads, aiming to minimize the investment and operation and maintenance costs of photovoltaics and energy storage, while maximizing the annual income of photovoltaics; by introducing a box-type uncertainty set to describe the uncertainty range of load and photovoltaic output, and introducing uncertainty parameters to regulate the conservative degree of the optimal solution, the flexibility and adaptability of the planning scheme are improved. The present invention also fully considers energy storage constraints, power balance constraints and voltage and current constraints, ensuring the stability and reliability of the planning scheme in actual operation.

[0099] S106: The reliability index calculation layer calculates the reliability index according to the line planning scheme and the source-storage addressing and capacity determination scheme, and returns the reliability index calculation result to the source-storage addressing and capacity determination layer and the cluster line planning layer. The cluster line planning layer, the source-storage addressing and capacity determination layer and the reliability index calculation layer repeatedly iterate to solve and obtain the optimal cluster division scheme;

[0100] Preferably, a reliability index is calculated according to the line planning scheme and the source-storage addressing and sizing scheme, and the reliability index is the power outage loss cost of the user;

[0101] Preferably, the objective function of the reliability index calculation layer is established with the goal of minimizing the power outage loss cost of users. The objective function of the reliability index calculation layer is expressed as:

[0102]

[0103] Among them, ECOST is the power outage loss cost for users in cluster k, λ j is the failure rate of the jth node, i.e., the average number of power outages, r j is the average power outage time of the jth node failure, is the average load value of node j, N n,l is the total number of nodes connecting branches in cluster k, H j is the loss cost caused by power outage of the average load of node j, is the maximum interruption time of the average load of node j, is the maximum interruption of the average load of node j;

[0104] Preferably, based on the probability of cluster island operation, the node failure rate and the average power outage time of node failure of different types of cluster tie switches are calculated by the minimum path method and breadth-first search method principles;

[0105] Preferably, the reliability index is calculated according to the node failure rate and the average power outage time of node failure of different types of cluster tie switches in combination with the reliability index calculation layer constraints;

[0106] In the embodiment of the present application, after the distribution network is divided into clusters, it is necessary to consider the probability of cluster island operation and the problem of node subordination to the cluster to be planned. The reliability index method based on the minimum path method of the present invention considers the reliability index calculation problem under cluster planning; Figure 2 As a schematic diagram of a simple distribution network after cluster division, the distribution network includes a main network, branch nodes and multiple load lines; the main network, that is, the connection network between the substation and the branch nodes, covers key equipment such as distribution lines, disconnectors, circuit breakers and transformers; the branch network is the connection system between the branch nodes and each load point, forming a branch network of the distribution network;

[0107] Depend on Figure 3 As shown, Figure 3 In (a), the main networks are l1-l6, d1 and d2, and the branch networks are l7-l14, d3, G1-G3, f1-f2. Multiple branch networks may correspond to only one branch node. Figure 3 The distribution network cluster division shown in (a) and the source-grid-load-storage planning based on dynamic cluster division using the method in this chapter are obtained Figure 3 (b) Figure 3 As shown in (b), different clusters contain various networks, and the distribution is relatively reasonable. When distributed renewable energy is connected to the nodes in the cluster, the cluster has a probability of realizing island operation. Therefore, when calculating the reliability index, it is necessary to calculate the probability of the cluster realizing island operation. According to the minimum path method and breadth-first search method of the present invention, the reliability index can be calculated.

[0108] pass Figure 3 (b) It can be seen that the branch network containing the cluster is connected to the main network through the branch node. When the main network element outside the cluster fails, it can be connected by transmitting instructions to the connecting switch. The connecting switch can be an isolating switch or a circuit breaker. When the switch is disconnected, the cluster has a probability of island operation. Therefore, the calculation of the reliability index needs to be discussed for the connecting switch. The specific parameters of the circuit breaker and the isolating switch are different. Therefore, the calculation process of the reliability index is analyzed in two specific cases.

[0109] Case 1: If the cluster tie switch is a circuit breaker, the failure rate and average power outage time of the jth node are expressed as:

[0110] Minimal path:

[0111]

[0112] Non-minimal path:

[0113]

[0114] Among them, λ j is the failure rate of the jth node, i.e., the average number of power outages, r j is the average power outage time of the jth node failure, is the probability of cluster island operation, which reflects the possibility that the photovoltaic and energy storage systems connected to cluster k can meet the load demand when cluster k enters the island operation state. k is the circuit breaker failure rate, e j is the failure rate of component j, e p is the photovoltaic failure rate, N n,k is the number of nodes in cluster k, N p,k is the number of PV nodes in cluster k, is the fault repair time of component i, is the fault repair time of the PV node, e i is the failure rate of component i;

[0115] Case 2: If the cluster tie switch is an isolating switch, the failure rate and average power outage time of the jth node are expressed as:

[0116] Minimal path:

[0117]

[0118] Non-minimal path:

[0119]

[0120] μ j =r j / λ j

[0121] Among them, λ j is the failure rate of the jth node, i.e., the average number of power outages, r j is the average power outage time of the jth node failure, is the probability of cluster island operation, which reflects the possibility that the photovoltaic and energy storage systems connected to cluster k can meet the load demand when cluster k enters the island operation state. k is the circuit breaker failure rate, e j is the failure rate of component j, e p is the photovoltaic failure rate, N n,k is the number of nodes in cluster k, N p,k is the number of PV nodes in cluster k, is the fault repair time of component i, is the fault repair time of the PV node, e iis the failure rate of component i, r break is the operating time of the disconnector, e k1 is the failure rate of the isolating switch;

[0122] Set G as a variable to determine whether there is an isolating switch. If the branch node is an isolating switch, it is 1; otherwise, it is 0. When the cluster tie switch is an isolating switch, the failure rate and average power outage time of the jth node can be written as follows:

[0123]

[0124]

[0125] Non-minimal path:

[0126]

[0127] Among them, λ j is the failure rate of the jth node, i.e., the average number of power outages, r j is the average power outage time of the jth node failure, is the probability of cluster island operation, which reflects the possibility that the photovoltaic and energy storage systems connected to cluster k can meet the load demand when cluster k enters the island operation state. k is the circuit breaker failure rate, e j is the failure rate of component j, e p is the photovoltaic failure rate, N n,k is the number of nodes in cluster k, N p,k is the number of PV nodes in cluster k, is the fault repair time of component i, is the fault repair time of the PV node, e i is the failure rate of component i, r break is the operating time of the disconnector, e k1 is the failure rate of the isolating switch;

[0128] Thus, the calculation expressions of node failure rate and average power outage time due to node failure are obtained. After analyzing the distribution network, the specific values ​​can be obtained, so as to calculate the power outage loss cost of users.

[0129] Preferably, the reliability indicator calculation layer constraints include the maximum interruption time of the average node load and the maximum interruption amount of the average node load. The node load interruption time and the average node load interruption amount must meet the following requirements:

[0130]

[0131] in, is the upper limit of the maximum interruption of the average load of node j, is the upper limit of the maximum interruption time of the average load of node j, is the average load interruption time of node j;

[0132] It should be noted that the present invention constructs a reliability index calculation layer by integrating the line planning scheme and the source-storage addressing and sizing scheme, and comprehensively evaluates the reliability of the distribution network with the goal of minimizing the user's power outage loss cost. It not only considers the impact of cluster division on power supply reliability, but also deeply analyzes the probability of cluster island operation and the impact of different types of contact switches on failure rate and power outage time, thereby improving the accuracy and practicality of reliability evaluation; by introducing the minimum path method and breadth-first search method, the failure rate and average power outage time of the node are scientifically calculated, providing strong support for the formulation of more reasonable cluster division and source-storage configuration strategies; at the same time, the present invention also sets constraints on the reliability index calculation layer to ensure that the node load interruption time and interruption amount are within an acceptable range, further improving the overall operation reliability and user satisfaction of the distribution network;

[0133] It should also be noted that, based on the distribution network data and characteristics, the present invention establishes a multi-level planning model, the upper layer of the multi-level planning model is the cluster line planning layer, the middle layer is the source-storage addressing and sizing layer, and the lower layer is the reliability index calculation layer; in the planning process, the upper-level planning first completes the line planning, and passes the result as the initial condition to the middle-level planning. After receiving the information transmitted by the upper layer, the middle-level planning further makes decisions on the addressing and sizing of distributed photovoltaics and energy storage; at the same time, the middle-level planning feeds back the photovoltaic, energy storage and load parameters to the upper-level planning to meet the flow constraints and cluster penetration constraints, and on the other hand, passes the photovoltaic, energy storage and load parameters to the lower layer; after determining the distributed photovoltaic and energy storage, and the line direction, the lower layer calculates the reliability index based on the given parameters, and returns the result to the middle layer, the upper, middle and lower layers repeatedly iterate to solve until the optimal result is obtained. The solution process of the multi-level planning model is as follows Figure 4 shown.

[0134] The above is a schematic scheme of a method for planning a multi-level cluster of a distribution network considering power supply reliability in this embodiment. It should be noted that the technical scheme of the system for planning a multi-level cluster of a distribution network considering power supply reliability and the technical scheme of the method for planning a multi-level cluster of a distribution network considering power supply reliability belong to the same concept. For details not described in detail in the technical scheme of the system for planning a multi-level cluster of a distribution network considering power supply reliability in this embodiment, please refer to the description of the technical scheme of the method for planning a multi-level cluster of a distribution network considering power supply reliability.

[0135] The multi-level cluster planning system for a distribution network considering power supply reliability in this embodiment includes:

[0136] A multi-level model building module is used to build a multi-level planning model, which includes a cluster line planning layer, a source-storage addressing and capacity determination layer, and a reliability index calculation layer;

[0137] The cluster line planning module is used to establish the objective function of the cluster line planning layer based on the photovoltaic and load forecast values ​​of the distribution network, with the goal of minimizing the line planning cost and network loss cost, and solve the objective function of the cluster line planning layer to obtain the line planning solution;

[0138] The source-storage addressing and capacity determination module is used to establish the source-storage addressing and capacity determination layer objective function based on the line planning scheme, with the goal of minimizing the annual investment and operation and maintenance costs of photovoltaics, the annual income of photovoltaics, and the annual investment cost of energy storage, and solve the source-storage addressing and capacity determination layer objective function to obtain the source-storage addressing and capacity determination scheme;

[0139] A reliability index calculation module is used for the reliability index calculation layer to calculate the reliability index according to the line planning scheme and the source-storage addressing and capacity determination scheme;

[0140] The optimal cluster partitioning scheme acquisition module is used to return the reliability index calculation results to the source-reservoir addressing and capacity determination layer and the cluster line planning layer. The cluster line planning layer, the source-reservoir addressing and capacity determination layer and the reliability index calculation layer repeatedly iterate to obtain the optimal cluster partitioning scheme.

[0141] This embodiment further provides a computing device, which is applicable to a case where multi-level cluster planning of a distribution network is considered with power supply reliability, and includes:

[0142] A memory and a processor; the memory is used to store computer executable instructions, and the processor is used to execute computer executable instructions to implement the multi-level cluster planning method for the distribution network considering power supply reliability as proposed in the above embodiment.

[0143] This embodiment also provides a storage medium on which a computer program is stored. When the program is executed by a processor, the method for planning a multi-level cluster of a distribution network taking into account power supply reliability as proposed in the above embodiment is implemented.

[0144] The storage medium proposed in this embodiment and the method for implementing a multi-level cluster planning of a distribution network considering power supply reliability proposed in the above embodiment belong to the same inventive concept. The technical details not described in detail in this embodiment can be referred to the above embodiment, and this embodiment has the same beneficial effects as the above embodiment.

[0145] Through the above description of the implementation methods, the technicians in the relevant field can clearly understand that the present invention can be implemented by means of software and necessary general hardware, and of course can also be implemented by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as a computer floppy disk, read-only memory (ReadOnly, Memory, ROM), random access memory (RandomAccess Memory, RAM), flash memory (FLASH), hard disk or optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform the methods of various embodiments of the present invention.

[0146] Example 2

[0147] Reference Figure 5-9 and Table 1, are an embodiment of the present invention, which provides a multi-level cluster planning method for a distribution network considering power supply reliability. In order to verify its beneficial effects, experimental verification results are provided.

[0148] In order to verify the practicality of the present invention, this embodiment uses a real power distribution network in China as an example to carry out simulation verification;

[0149] The total load access capacity of the distribution network is 22.8MVA, and the total photovoltaic power access capacity is 7.5MW. The geographical layout of the distribution network is as follows: Figure 5 As shown, the total length of the lines to be planned reaches 329.82km.

[0150] In order to verify the flexible and adjustable ability of the dynamic partitioning method of the present invention in terms of the conservatism of the adjustment scheme, three groups of uncertain adjustment parameters are selected and compared from the aspects of network connection scheme, energy storage access capacity, photovoltaic access capacity and total planning cost;

[0151] Uncertainty adjustment parameters Γ of active load power and reactive load power in three groups of models PL , Γ QL , PV output uncertainty adjustment parameter Γ PV The selection results are as follows:

[0152] Solution 1: Choose Γ PL =Γ QL =0,Γ PV =0, in which case the active load power, reactive load power and PV output are all equal to the predicted values.

[0153] Solution 2: Choose Γ PL =Γ QL =30, ΓPV =10. In this case, during the planning process, 30 nodes have the minimum values ​​of active load power and reactive load power in the prediction interval, and 10 nodes have the maximum values ​​of photovoltaic output in the prediction interval.

[0154] Solution 3: Choose Γ PL =Γ QL =75, Γ PV =20, which is the worst case among all robust planning schemes. There are 75 nodes with the minimum values ​​of active load power and reactive load power in the prediction interval, and there are 20 nodes with the maximum values ​​of photovoltaic output in the prediction interval.

[0155] The PV planning capacity and energy storage access capacity under the three groups of situations are as follows: Figure 6 , Figure 7 As shown;

[0156] according to Figure 6 As shown in the figure, with the increase of uncertainty adjustment parameters, the PV planning capacity in the planning results shows a trend of gradual reduction. This is mainly due to the increasingly severe conditions. In order to ensure the reliability of power supply and the economy of the planning scheme and maintain the normal operation of the cluster, the PV access volume must be reduced accordingly to ensure that the PV penetration rate of the cluster remains at a low level.

[0157] Further observation Figure 7 It can be found that as the conservatism of the planning scheme increases, the energy storage access capacity is also gradually increasing. This is because compared with Scheme 1, Schemes 2 and 3 have smaller active power loads and reactive power loads, while photovoltaic output is larger. Therefore, more energy storage systems are needed to balance the uncertainty of photovoltaic output.

[0158] The average number of power outages and average power outage time of nodes under the three groups of scenarios are as follows: Figure 8 , Fig. 9 As shown;

[0159] Depend on Figure 8 , Fig. 9 It is concluded that with the increase of the uncertainty adjustment parameter, the average number of power outages and the average power outage time of the nodes under different schemes also increase accordingly. With the increase of uncertainty, the obtained schemes become more and more conservative, the reliability indicators of the nodes decrease, and the average power outage time and the average number of power outages of the nodes all increase; this is because the divided clusters are changing, and the power supply duration is different, which makes the reliability indicators vary greatly; when the uncertainty increases, in order to ensure the safe, stable and economical operation of the cluster, it is necessary to increase the conservatism of the scheme.

[0160] The specific costs are shown in Table 1, where A represents the annual investment and operation and maintenance costs of photovoltaic power generation (10,000 RMB), B represents the annual revenue costs of photovoltaic power generation (10,000 RMB), C represents the line planning costs (10,000 RMB), D represents the annual network loss costs of clusters (10,000 RMB), E represents the annual investment costs of energy storage (10,000 RMB), F represents the user's power outage loss costs (10,000 RMB), and G represents the total costs (10,000 RMB);

[0161] Table 1 Planning costs under different schemes

[0162]

[0163] In addition, through in-depth analysis of the data in Table 1, it can be observed that as the uncertainty parameter adjustment gradually increases, although the annual investment and operation and maintenance costs of photovoltaic power generation have decreased, the annual income of photovoltaic power generation has shown a downward trend;

[0164] At the same time, the annual network investment costs, network losses, annual energy storage investment costs, and user power outage loss costs have also increased accordingly. The main reason behind this phenomenon is that when the uncertainties faced by the distribution network are more fully considered during the planning process, the resulting planning schemes tend to be more conservative; although this conservatism helps to deal with potential risks, it will also lead to an increase in power outage losses, thereby leading to an increase in total costs.

[0165] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. 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 multi-level cluster planning method for a distribution network considering power supply reliability, characterized in that: include: Acquire distribution network data, perform initial cluster division according to the distribution network data and establish a multi-level planning model, wherein the multi-level planning model includes a cluster line planning layer, a source-storage addressing and capacity determination layer, and a reliability index calculation layer; Based on the photovoltaic and load forecast values ​​of the distribution network, with the goal of minimizing the line planning cost and network loss cost, a cluster line planning layer objective function is established, and the cluster line planning layer objective function is solved to obtain a line planning solution; Based on the line planning scheme, with the goal of minimizing the annual investment and operation and maintenance costs of photovoltaics, the annual income of photovoltaics, and the annual investment cost of energy storage, a source-storage addressing and capacity-fixing layer objective function is established, and the source-storage addressing and capacity-fixing layer objective function is solved to obtain the source-storage addressing and capacity-fixing scheme; The reliability index calculation layer calculates the reliability index according to the line planning scheme and the source-reservoir addressing and sizing scheme, and returns the reliability index calculation result to the source-reservoir addressing and sizing layer and the cluster line planning layer. The cluster line planning layer, the source-reservoir addressing and sizing layer and the reliability index calculation layer repeatedly iterate to obtain the optimal cluster division scheme.

2. The method for planning a multi-level cluster of a distribution network considering power supply reliability according to claim 1, characterized in that: The objective functions of cluster line planning layer include: Based on the initial cluster division results and the photovoltaic and load forecast values, the distribution network line is expanded and planned with the goal of minimizing the line planning cost and network loss cost, and the cluster line planning layer objective function is established. The cluster line planning layer objective function is expressed as: min f=F1+F2 Among them, F1 is the annual investment cost of the network, F2 is the network power transmission loss cost, Ω s is the set of nodes in the branch network, is the set of child nodes of node i, C l Indicates the investment cost per kilometer of the line, D ij refers to the length of the line between nodes i and j, x ij is a 0-1 variable for the line between nodes i and j, where 1 indicates that the line has been installed, 0 indicates that the line has not been installed, χ indicates the bank interest rate, β indicates the investment payback period, and C e represents the electricity price, N n,k Indicates the number of nodes contained in cluster k, i ij,t represents the square value of the current in the line between nodes i and j at time t, ε ij Represents the line resistance value between nodes i and j.

3. The method for planning a multi-level cluster of a distribution network considering power supply reliability according to claim 1 or 2, characterized in that: The objective function for establishing source-reservoir location and volume determination layer includes: Based on the line planning scheme and combined with the uncertainty of photovoltaic and load, the investment and operation and maintenance costs of the source-storage in the cluster are minimized, and the source-storage addressing and capacity-fixed layer objective function is established. The source-storage addressing and capacity-fixed layer objective function is expressed as: minF=F3-F4+F5 Among them, F3 is the annual investment and operation and maintenance cost of photovoltaic in cluster k, F4 is the annual income of photovoltaic in cluster k, F5 is the annual investment cost of energy storage in cluster k, and C PV is the investment cost per MW of photovoltaic power, C OMPV is the annual fixed maintenance cost per MW PV, П k is the set of nodes contained in cluster k, S PV,j is the original planned PV capacity of node j in cluster k, S PVf,j is the planned PV capacity added to node j in cluster k, C sell and C sub are the grid-connected electricity price and subsidized electricity price of distributed power sources, ω PV,t is the maximum output of photovoltaic power per megawatt under given sunshine conditions at time t, ρ is the discount rate, r is the number of years of discount, c bat is the investment cost per unit capacity of energy storage, P batt,j Configure the energy storage capacity for node j.

4. The method for planning a multi-level cluster of a distribution network considering power supply reliability as claimed in claim 3, characterized in that: Uncertainties in PV and load include, The box-type uncertainty set is used to obtain the uncertainty range of active load power, reactive load power and photovoltaic output, and the uncertainty parameters are introduced to regulate the configuration strategy of the source-storage addressing and sizing scheme.

5. The method for planning a multi-level cluster of a distribution network considering power supply reliability as claimed in claim 4, characterized in that: Reliability index calculation includes, Calculating a reliability index according to the line planning scheme and the source-storage addressing and sizing scheme, wherein the reliability index is the power outage loss cost for the user; The objective function of the reliability index calculation layer is established with the goal of minimizing the power outage loss cost of users. The objective function of the reliability index calculation layer is expressed as: Among them, ECOST is the power outage loss cost for users in cluster k, λ j is the failure rate of the jth node, i.e., the average number of power outages, r j is the average power outage time of the jth node failure, is the average load value of node j, N n,l is the total number of nodes connecting branches in cluster k, H j is the loss cost caused by power outage of the average load of node j, is the maximum interruption time of the average load of node j, is the maximum interruption of the average load of node j.

6. The method for planning a multi-level cluster of a distribution network considering power supply reliability according to claim 5, characterized in that: Also includes, Based on the probability of cluster island operation, the node failure rate and average power outage time of different types of cluster tie switches are calculated using the minimum path method and breadth-first search method. The reliability index is calculated according to the node failure rate and the average power outage time of the node failure of the different types of cluster tie switches in combination with the reliability index calculation layer constraints.

7. The method for planning a multi-level cluster of a distribution network considering power supply reliability according to claim 6, characterized in that: The reliability index calculation layer constraints include: The constraints of the reliability index calculation layer include the maximum interruption time of the average node load and the maximum interruption amount of the average node load. The node load interruption time and the average node load interruption amount must meet the following requirements: in, is the upper limit of the maximum interruption of the average load of node j, is the upper limit of the maximum interruption time of the average load of node j, is the average load interruption time of node j.

8. A system for multi-level cluster planning of distribution network considering power supply reliability, characterized in that: include, A multi-level model building module, used to build a multi-level planning model, wherein the multi-level planning model includes a cluster line planning layer, a source-reservoir addressing and capacity determination layer, and a reliability index calculation layer; The cluster line planning module is used to establish a cluster line planning layer objective function based on the distribution network photovoltaic and load forecast values, with the goal of minimizing line planning cost and network loss cost, and solve the cluster line planning layer objective function to obtain a line planning solution; A source-storage addressing and capacity determination module is used to establish a source-storage addressing and capacity determination layer objective function based on the line planning scheme, with the goal of minimizing the annual investment and operation and maintenance costs of photovoltaics, the annual income of photovoltaics, and the annual investment cost of energy storage, and solve the source-storage addressing and capacity determination layer objective function to obtain a source-storage addressing and capacity determination scheme; A reliability index calculation module, used for the reliability index calculation layer to calculate the reliability index according to the line planning scheme and the source-storage addressing and capacity determination scheme; The optimal cluster partitioning scheme acquisition module is used to return the reliability index calculation results to the source-reservoir addressing and capacity determination layer and the cluster line planning layer. The cluster line planning layer, the source-reservoir addressing and capacity determination layer and the reliability index calculation layer repeatedly iterate to obtain the optimal cluster partitioning scheme.

9. An electronic device, comprising: Memory and processor; The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions. When the computer-executable instructions are executed by the processor, the steps of the distribution network multi-level cluster planning method considering power supply reliability as described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the steps of the distribution network multi-level cluster planning method considering power supply reliability as described in any one of claims 1 to 7.

Images