Power distribution network planning method and system adapted to new energy access

Abstract

The invention discloses a power distribution network planning method and system suitable for new energy access, and relates to the technical field of power distribution network planning, and the method comprises the steps: obtaining a new energy node of island power generation in a power distribution network, calculating power transmission loss data and new energy permeability from the island power generation nodes to the total power distribution network and the nearest power distribution sub-network, constructing a node input model by using a particle swarm optimization algorithm, determining a power transmission mode and an access node, and if the nearest power distribution sub-network is selected for access, obtaining a stable shortage period set; obtaining a time matching degree by adopting a calculation method based on a time window and entropy, judging whether time periods are matched or not, and reselecting an access node when the time periods are not matched; the invention also provides a power distribution network planning system adapted to new energy access. The system comprises a time period acquisition module, a stability analysis module, a model establishment module, a matching judgment module and a node determination module. According to the invention, optimization of planning of new energy access to the power distribution network is facilitated.

Description

Technical Field

[0001] The present invention relates to the technical field of distribution network planning, and in particular to a distribution network planning method and system adapted to the access of new energy sources. Background Art

[0002] In the current field of distribution network planning, with the large-scale access of new energy sources, traditional planning methods have gradually exposed many shortcomings.

[0003] In the existing technology, transmission losses, new energy penetration rate and the matching of power generation and power consumption periods are not comprehensively considered. When selecting transmission paths and access nodes, the existing technology ignores the losses of new energy access nodes and distribution network subnet nodes based on simple distance or capacity standards, resulting in large energy losses in the transmission process and reducing the penetration rate of new energy in the distribution network.

[0004] In the existing technology, in dealing with the dynamic changes of new energy access in the distribution network, the flexibility and adaptability of the existing technology are poor. When the initially selected access node does not match the power shortage period, the planning scheme cannot be adjusted and the appropriate access node or transmission path cannot be reselected, which limits the access planning of new energy in the distribution network.

[0005] To this end, the present invention provides a distribution network planning method and system that is adaptable to the access of new energy sources. Summary of the invention

[0006] The object of the present invention is to provide a distribution network planning method and system adapted to the access of new energy sources, so as to solve at least one of the above-mentioned problems of the prior art.

[0007] In a first aspect, the present invention provides a distribution network planning method adapted to the access of new energy sources, comprising the following steps: Step 1: Obtain the new energy nodes of isolated power generation in the distribution network, integrate the power generation surplus periods of the isolated power generation nodes, and build a power generation surplus schedule; Step 2: Perform numerical analysis on the power generation surplus time periods of all monitoring cycles, determine the stable surplus time periods, and store the stable surplus time in the power generation surplus time table into the stable surplus time set; Step 3: Based on the stable surplus time set, obtain the nearest distribution subgrid in the distribution network, and build a node input model to determine whether the nearest distribution subgrid can be used as an input access node for the isolated power generation node; Step 4: If the nearest distribution grid can be used as an input access node for the isolated power generation node, perform numerical analysis on the stable power shortage period of the nearest distribution grid to determine whether the stable shortage period of the nearest distribution grid matches the stable surplus period of the isolated power generation node.

[0008] As a further technical solution of the present invention: the method for obtaining the stable surplus period is: Numerical analysis is performed on the power generation surplus periods of all monitoring cycles to obtain the surplus period ratio Ys and the intermittent period ratio Jd; By formula: Get the steady-state value W of the time period, where α1 and α2 are preset proportional coefficients; If the period steady-state value W is higher than the period steady-state threshold, the power generation surplus period of the historical monitoring period is marked as a stable surplus period.

[0009] As a further technical solution of the present invention: the surplus period ratio Ys is obtained in the following manner: Extract each column in the power generation surplus schedule as a single column of surplus period, and use the sliding window method to obtain the number of consecutive occurrences of surplus discontinuity periods; Obtain the number of power generation surplus periods in the surplus period column, perform ratio processing on the number of power generation surplus periods and the number of monitoring cycles to obtain the surplus period ratio, and mark the surplus period ratio as Ys; The discontinuity period ratio Jd is obtained by averaging the number of consecutive occurrences of surplus discontinuity periods in the surplus period column to obtain the mean of the discontinuity periods; The intermittent period ratio is obtained by ratio processing the mean value of the intermittent period to the number of monitoring cycles, and the intermittent period ratio is marked as Jd.

[0010] As a further technical solution of the present invention: whether the nearest power distribution network can be used as an input access node of the isolated power generation node is determined as follows: Based on the power topology, the nearest distribution network to the isolated power generation node is obtained, and the nearest distribution network is obtained. Based on the node input model, the adaptive function between the distribution network that reaches the node upper limit value and the nearest distribution network is obtained. ; If the distribution network Lower than the nearest distribution network , the nearest distribution network is used as the input access node of the island generation node.

[0011] As a further technical solution of the present invention: the node input model is constructed as follows: Based on the stable surplus period set, the transmission loss data of the isolated power generation node to the main distribution grid and the nearest distribution subgrid during the stable surplus period is obtained; By formula: Obtain the theoretical loss of three-phase AC power from the island power generation node to the distribution network node ; Where P represents the power generation of the isolated power generation node during the stable surplus period, U is the voltage, represents the power factor, ρ is the resistivity of the transmission line, L is the length of the transmission line, and S is the area of ​​the transmission line; The new energy power input load of the distribution network is processed by ratio with the total power input load in the distribution network to obtain the new energy penetration rate, which is marked as St; Based on the particle swarm optimization algorithm and the theoretical loss of three-phase AC power from the isolated power generation node to the distribution network node , new energy penetration rate, steady-state value W of the period, determine the fitness function , build the node input model.

[0012] As a further technical solution of the present invention: the fitness function The establishment method is: , where β1, β2, and β3 are preset proportional coefficients, Represents the theoretical loss of three-phase AC power in different stable surplus periods , new energy penetration rate, and the maximum value of the steady-state value W during the period.

[0013] As a further technical solution of the present invention: the method for determining whether the stable shortage period of the nearest power distribution network matches the stable surplus period of the isolated power generation node is as follows: By formula: Obtain the time matching degree Pd, where H1 and H2 are the entropies of the stable shortage period set and the stable surplus period set respectively, and max(H1, H2) represents the maximum entropy of the stable shortage period set and the stable surplus period set; If the time matching degree Pd is higher than the time matching degree threshold, the stable shortage period of the nearest distribution network matches the stable surplus period of the island generation node.

[0014] As a further technical solution of the present invention: the entropy H1 of the stable shortage period set and the entropy H2 of the stable surplus period set are obtained as follows: Based on the energy management system of the distribution network, the stable shortage period of the distribution network in all monitoring periods is obtained and stored in the stable shortage period set; Based on the stable shortage period set and the stable surplus period set, the time matching degree is obtained by using the time window and entropy calculation method; Determine the time shear window Δt, divide the monitoring period into multiple time matching windows, and construct the time matching window set S q ={s1, s2, ..., s t}, q is the number of the time matching window set, and the value range of q is [1, t]; Obtain the frequencies f1 and f2 of all time windows including stable shortage periods and stable surplus periods, and obtain the entropies H1 and H2 of the stable shortage period set and stable surplus period set through the information entropy formula.

[0015] As a further technical solution of the present invention: a distribution network planning method adapted to the access of new energy sources further includes the following steps: Step 5: If the recent stable shortage period of the distribution network does not match the stable surplus period of the isolated power generation node, obtain other distribution network nodes in the power topology map, combine the distribution network node input to the node input model, and determine the input access node of the isolated power generation node.

[0016] In a second aspect, the present invention provides a distribution network planning system adapted to the access of new energy sources, comprising the following modules: Time period collection module: The time period collection module is used to obtain the new energy nodes of isolated power generation in the distribution network, integrate the power generation surplus time periods of the isolated power generation nodes, and build a power generation surplus schedule; Stability analysis module: The stability analysis module is used to perform numerical analysis on the power generation surplus period of the entire monitoring cycle, determine the stable surplus period, and establish a stable surplus time set; Model building module: The model building module is used to build a node input model to determine whether the nearest distribution network can serve as an input access node for the island generation node; Matching judgment module: If the nearest distribution network is used as the input access node of the isolated power generation node, the matching judgment module is used to perform numerical analysis on the power load of the nearest distribution network to determine whether the stable shortage period of the nearest distribution network matches the stable surplus period of the isolated power generation node; Node determination module: If there is no match, the node determination module is used to obtain other distribution network nodes in the power topology diagram, combine the distribution network node input to the node input model, and determine the input access node of the isolated power generation node.

[0017] Beneficial effects of the present invention: 1. By integrating and analyzing the surplus power periods of isolated power generation nodes, stable surplus periods can be identified, so that new energy power generation nodes can be more targetedly connected to the distribution network, reducing energy waste caused by the mismatch between power generation periods and power consumption periods; 2. The node input model constructed by the particle swarm optimization algorithm comprehensively considers the transmission loss, new energy penetration rate and steady-state value of the time period to determine the transmission mode and access node. It can find the optimal or near-optimal input node in a complex distribution network environment. This multi-factor optimization technology can find the new energy input node with the smallest energy loss during the transmission process.

[0018] 3. When determining the access node of an isolated power generation node, priority is given to not only the nearest distribution network, but also the most suitable access point is determined comprehensively by calculating its power load and the degree of matching with the stable surplus period. When the nearest distribution network does not meet the matching conditions, other distribution network nodes are obtained from the power topology map and re-evaluated. The idea of ​​dynamic adjustment enables the distribution network planning to adapt to the input of different new energy nodes into the distribution network. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0020] Figure 1 is a flow chart of a power generation surplus analysis method provided in Embodiment 1 of the present invention; Figure 2 This is a flowchart of the node analysis and determination method provided in the second embodiment of the present invention. Figure 3 is a flowchart of node matching judgment in Embodiment 2 of the present invention; Figure 4 This is a module diagram of a distribution network planning system adapted to the access of new energy sources provided in the third embodiment of the present invention; Figure 5 It is a structural diagram of a computer device provided in Embodiment 4 of the present invention. DETAILED DESCRIPTION

[0021] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention. Embodiment 1

[0022] like Figure 1 As shown, the present invention provides a distribution network planning method adapted to the access of new energy, which specifically includes the following steps: Step 1: Obtain the new energy nodes of isolated power generation in the distribution network, integrate the power generation surplus periods of the isolated power generation nodes, and build a power generation surplus schedule; In some embodiments, a topological diagram of the distribution network is constructed to obtain the type of the new energy generation node in the distribution network; Based on the type of renewable energy generation nodes, renewable energy generation nodes that cannot be connected to the grid for power generation are marked as isolated generation nodes; It should be noted that the island generation node independently supplies power to a region and does not transmit power to the public grid through regional power connection lines; The energy management system (EMS) is used to obtain historical power generation data of isolated power generation nodes, and the time periods when the power generation power is higher than the power load are marked as power generation surplus periods. Divide historical data into multiple monitoring periods according to time to obtain the power generation surplus period within all monitoring periods; Construct a power generation surplus schedule based on the power generation surplus periods of the entire monitoring period; Among them, each column of the power generation surplus schedule represents a different time period of the monitoring cycle. If the time period is a power generation surplus period, fill in "1" for the time period corresponding to the power generation surplus schedule, otherwise, fill in "0"; It should be noted that the period of surplus power generation filled in with “0” is the period of surplus intermittent power generation; Each column of the generation surplus schedule represents a different monitoring period; Step 2: Based on the power generation surplus schedule, numerical analysis is performed on the power generation surplus time periods of all monitoring cycles to determine the stable surplus time periods, and all the stable surplus times of the power generation surplus schedule are put into the stable surplus time set; Extract each column in the generation surplus schedule as a separate column for the surplus period; Use the sliding window method, define the sliding window size k, slide the window in the order of the profit period column from top to bottom, and count the number of consecutive occurrences of the profit period column and the profit discontinuity period in the window; Preferably, the sliding window k=3 is set; For example, for each position i in a single column of a surplus period, check the number of 0s in [i, i+k-1] in the sliding window. If the sliding window detects "0", it continues to slide. If it detects "1", it stops sliding the window. Record the number of consecutive non-zeros, that is, the number of consecutive occurrences of surplus discontinuity periods. For example, the profit period is listed as: [1,{0,0},1,0,....,0,1] T， Among them, {0,0} represents the continuous profit discontinuity period of the sliding window; The number of consecutive occurrences of profit discontinuity periods in the profit period column is averaged to obtain the mean of the discontinuity periods; The intermittent period mean value is processed by ratio with the number of monitoring cycles to obtain the intermittent period ratio, which is marked as Jd; Obtain the number of power generation surplus periods in the surplus period column, perform ratio processing on the number of power generation surplus periods and the number of monitoring cycles to obtain the surplus period ratio, and mark the surplus period ratio as Ys; Calculate the period steady-state value W based on the surplus period ratio Ys and the discontinuity period ratio Jd; By formula: Get the steady-state value W for the period, α1=0.125, α2=0.341; Compare the period steady-state value W with the period steady-state threshold to determine the stable surplus period within the entire monitoring period; If the time period steady-state value W is higher than the time period steady-state threshold, the power generation surplus period of the historical monitoring period is marked as a stable surplus period, otherwise, no processing is done; Based on the power generation surplus schedule, the stable surplus periods of all monitoring periods are obtained, and a stable surplus period set is constructed; The technical solution of this embodiment is: obtain new energy nodes for island power generation in the distribution network, integrate the power generation surplus time periods of the island power generation nodes, construct a power generation surplus timetable, and based on the power generation surplus timetable, perform numerical analysis on the power generation surplus time periods of all monitoring cycles to determine the stable surplus time periods, and put all the stable surplus times of the power generation surplus timetable into a stable surplus time set, which is beneficial to provide time analysis data for the distribution network access method of the subsequent island analysis nodes. Embodiment 2

[0023] like Figure 2 As shown, the present invention provides a distribution network planning method adapted to the access of new energy sources, further comprising the following steps: Step 3: Based on the stable surplus period set, a node input model is constructed to determine whether the nearest distribution network can serve as an input access node for the isolated power generation node; Based on the power topology map, the nearest distribution network closest to the isolated power generation node is obtained to obtain the nearest distribution network; Based on the stable surplus period set, the transmission loss data of the isolated power generation node to the main distribution grid and the nearest distribution subgrid during the stable surplus period is obtained; It should be noted that the total distribution network and the nearest distribution sub-network are obtained from the topological map of the distribution network; In some embodiments, the transmission loss is calculated based on the resistance and the transmission power of the transmission line; By formula: Obtain the theoretical loss of three-phase AC power from the island power generation node to the distribution network node ; Where P represents the power generation of the isolated power generation node during the stable surplus period, U is the voltage, represents the power factor, ρ is the resistivity of the transmission line, L is the length of the transmission line, and S is the area of ​​the transmission line; It should be noted that the length L of the transmission line is obtained from the topological diagram of the distribution network, the area S of the transmission line, the resistivity ρ of the transmission line, The power factor is set by professional technicians in this field, and the power generation power P and voltage U during the stable surplus period are obtained from the historical monitoring data of the isolated island power generation node; In some embodiments, the new energy power input load of the distribution network is processed by ratio processing with the total power input load in the distribution network to obtain the new energy penetration rate, and the new energy penetration rate is marked as St; Based on the particle swarm optimization algorithm, a node input model is constructed to determine the power transmission mode of the isolated power generation node; Specifically, the node input model is constructed as follows; S1. Construct the position vector X of each particle ij =(a ij , b ij 、c ij ); velocity vector v ij =(Va ij , Vb ij 、Vc ij ); Specifically, the position vector X ij =(a ij , b ij 、c ij ), i is the number of the particle, that is, the number of the distribution node (X1 represents the total distribution network, X2 represents the nearest distribution network), j represents the number of the stable surplus period, and a ij , b ij 、c ij Represents the theoretical loss of three-phase AC power in different stable surplus periods , new energy penetration rate, steady-state value W during the period; Velocity vector v ij It is randomly generated by a uniformly distributed random function according to the value range; Preferably, the value range is [-0.1, 0.1] S2. Constructing fitness function

[0024] Specifically, , where β1, β2, and β3 are 1.251, 0.562, and 0.21, respectively.

[0025] Represents the theoretical loss of three-phase AC power in different stable surplus periods , new energy penetration rate, and the maximum value of the steady-state value W during the period; S3, update the speed and position of iterative particles; The velocity update formula is: Update the speed and position of the iterative particle, where γ1 and γ2 are learning factors with a value range of (0,2), r1 and r2 are random numbers between [0,1], and p ij is the optimal weight of the individual particle, g ij is the optimal component of all particles, k is the number of iterations; S4, determine the iteration termination condition; When the number of iterations of the node input model reaches the upper limit, the algorithm stops; Preferably, the upper limit of the number of iterations is set to 100; Based on the node input model, obtain the total distribution network that reaches the node upper limit value Adaptive function with nearest distribution network ; If the distribution network Higher than the nearest distribution network , then the main distribution network is used as the input access node of the isolated power generation node, and vice versa, the nearest distribution network is used as the input access node of the isolated power generation node; Step 4: If the nearest distribution grid is used as the input access node of the isolated power generation node, a numerical analysis is performed on the power load of the nearest distribution grid to determine whether the stable shortage period of the nearest distribution grid matches the stable surplus period of the isolated power generation node; In some embodiments, the power load of the nearest power distribution network is obtained from the power grid monitoring system to obtain the power shortage period; Based on the acquisition method of the stable surplus period in step 1 and step 2, the electricity shortage period is numerically analyzed to obtain the stable shortage period; Obtain the stable and scarce time periods of all monitoring periods and put them into the stable and scarce time period set; Based on the stable shortage period set and the stable surplus period set, the time matching degree is obtained by using the time window and entropy calculation method; Determine the time shear window Δt, divide the monitoring period into multiple time matching windows, and construct the time matching window set S q ={s1, s2, ..., s t}, q is the number of the time matching window set, and the value range of q is [1, t]; Preferably, the time shear window Δt is 1 hour; Based on the stable and scarce time period set, obtain each time matching window set S q The number of stable shortage periods n q ; By formula: Get the frequency f1 of all time windows including the stable shortage period; Based on the stable surplus period set, obtain each time matching window set S q The number of stable profit periods m q ; By formula: Get the frequency f2 of all time windows including stable profit periods; By formula: Get the entropy H1 of the stable shortage period set; By formula: Obtain the entropy H2 of the stable profit period set; By formula: Get the time matching degree Pd; It should be noted that when Pd=1, |H1-H2|=0, that is, the entropy H1 of the stable shortage period set and the entropy H2 of the stable surplus period set are the same, indicating that the distribution patterns of the stable shortage period set and the stable surplus period set in the time window are exactly the same, and the time matching degree is the highest; When Pd=0, |H1-H2|=max(H1, H2), that is, the entropy H1 of the stable shortage period set and the entropy H2 of the stable surplus period set are the largest, that is, the distribution patterns of the stable shortage period set and the stable surplus period set in the time window are very different, and the time matching degree is the lowest; The time matching degree Pd is analyzed with the time matching degree threshold to determine whether the stable shortage period of the nearest power distribution network matches the stable surplus period of the isolated power generation node; If the time matching degree Pd is higher than the time matching degree threshold, it is considered that the stable shortage period of the nearest power distribution network matches the stable surplus period of the isolated power generation node, otherwise, it is not matched; Step 5: If the recent stable shortage period of the distribution network does not match the stable surplus period of the isolated power generation node, obtain other distribution network nodes in the power topology map, combine the distribution network nodes to input the node input model, and determine the input access node of the isolated power generation node; If the recent stable shortage period of the distribution subgrid does not match the stable surplus period of the isolated power generation node, other distribution subgrids are obtained from the power topology map and stored in the distribution subgrid data group; Based on the distribution network data group and the distribution network, the fitness function value of each distribution network in the distribution network data group is obtained by inputting it into the node input model. , the fitness function value of the distribution network ; like Figure 3 As shown, if the fitness function value of each distribution network in the distribution network data set is Higher than the fitness function value of the distribution network ; The fitness function value of each distribution network in the distribution network data set , sort them in descending order to determine the fitness function value The largest distribution subgrid serves as the input access node for the islanded generation nodes; If the fitness function value of each distribution network in the distribution network data set is Lower than the fitness function value of the distribution network , the main distribution network is used as the input access node of the island generation node; The technical solution of this embodiment is: based on the set of stable surplus time periods, a node input model is constructed to determine whether the nearest distribution subgrid can serve as the input access node of the isolated power generation node. If the nearest distribution subgrid serves as the input access node of the isolated power generation node, a numerical analysis is performed on the power load of the nearest distribution subgrid to determine whether the stable shortage period of the nearest distribution subgrid matches the stable surplus period of the isolated power generation node. If the stable shortage period of the nearest distribution subgrid does not match the stable surplus period of the isolated power generation node, other distribution subgrid nodes in the power topology map are obtained, and the input of the node input model is combined with the distribution main network node to determine the input access node of the isolated power generation node. The idea of ​​dynamic adjustment enables the distribution network planning to adapt to the input of different new energy nodes into the distribution network. Embodiment 3

[0026] like Figure 4 As shown, a distribution network planning system adapted to the access of new energy sources includes the following modules: Time period collection module: The time period collection module is used to obtain the new energy nodes of isolated power generation in the distribution network, integrate the power generation surplus time periods of the isolated power generation nodes, and build a power generation surplus schedule; Stability analysis module: The stability analysis module is used to perform numerical analysis on the power generation surplus time periods of all monitoring cycles, determine the stable surplus time periods, and put all the stable surplus times of the power generation surplus schedule into the stable surplus time set; Model building module: The model building module is used to build a node input model to determine whether the nearest distribution network can serve as an input access node for the island generation node; Matching judgment module: If the nearest distribution network is used as the input access node of the isolated power generation node, the matching judgment module is used to perform numerical analysis on the power load of the nearest distribution network to determine whether the stable shortage period of the nearest distribution network matches the stable surplus period of the isolated power generation node; Node determination module: If the recent stable shortage period of the distribution network does not match the stable surplus period of the isolated power generation node, the node determination module is used to obtain other distribution network nodes in the power topology map, combine the distribution network node input to the node input model, and determine the input access node of the isolated power generation node. Embodiment 4

[0027] Reference Figure 5 The embodiment of the present invention further provides a computer device 3, comprising: a memory 302 and a processor 301 and a computer program 303 stored in the memory 302. When the computer program 303 is executed on the processor 301, a distribution network planning method adapted to the access of new energy sources as described in any one of the above methods is implemented.

[0028] The computer device 3 may be a computing device such as a desktop computer, a notebook, a PDA, a cloud server, etc. The computer device 3 may include, but is not limited to, a processor 301 and a memory 302. Those skilled in the art may understand that; Figure 5 It is only an example of computer device 3 and does not constitute a limitation on computer device 3. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components, for example, it may also include input and output devices, network access devices, etc.

[0029] The processor 301 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc.

[0030] In some embodiments, the memory 302 may be an internal storage unit of the computer device 3, such as a hard disk or memory of the computer device 3. In other embodiments, the memory 302 may also be an external storage device of the computer device 3, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc. equipped on the computer device 3. Further, the memory 302 may also include both an internal storage unit of the computer device 3 and an external storage device. The memory 302 is used to store an operating system, an application program, a boot loader (BootLoader), data, and other programs, such as the program code of the computer program, etc. The memory 302 may also be used to temporarily store data that has been output or is to be output. Embodiment 5

[0031] An embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, a distribution network planning method adapted to the access of new energy sources as described in any one of the above methods is implemented.

[0032] In this embodiment, if the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present application implements all or part of the processes in the above-mentioned embodiment method, which can be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by the processor, the steps of the above-mentioned various method embodiments can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium can at least include: any entity or device that can carry the computer program code to the camera / terminal device, recording medium, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electric carrier signal, telecommunication signal and software distribution medium. For example, USB flash drive, mobile hard disk, disk or optical disk. In some jurisdictions, according to legislation and patent practice, computer-readable media cannot be electric carrier signals and telecommunication signals.

[0033] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0034] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0035] In the embodiments disclosed in the present application, it should be understood that the disclosed devices / terminal equipment and methods can be implemented in other ways. For example, the device / terminal equipment embodiments described above are only schematic. For example, the division of the modules or units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0036] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0037] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0038] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. A distribution network planning method adapted to the access of new energy sources, characterized in that: The following steps are involved: Step 1: Obtain the new energy nodes of isolated power generation in the distribution network, integrate the power generation surplus periods of the isolated power generation nodes, and build a power generation surplus schedule; Step 2: Perform numerical analysis on the power generation surplus time periods of all monitoring cycles, determine the stable surplus time periods, and store the stable surplus time in the power generation surplus time table into the stable surplus time set; Step 3: Based on the stable surplus time set, obtain the nearest distribution subgrid in the distribution network, and build a node input model to determine whether the nearest distribution subgrid can be used as an input access node for the isolated power generation node; Step 4: If the nearest distribution grid can be used as an input access node for the isolated power generation node, perform numerical analysis on the stable power shortage period of the nearest distribution grid to determine whether the stable shortage period of the nearest distribution grid matches the stable surplus period of the isolated power generation node.

2. A distribution network planning method adapted to the access of new energy sources according to claim 1, characterized in that: The method of obtaining the stable surplus period is as follows: Numerical analysis is performed on the power generation surplus periods of all monitoring cycles to obtain the surplus period ratio Ys and the intermittent period ratio Jd; By formula: Get the steady-state value W of the time period, where α1 and α2 are preset proportional coefficients; If the period steady-state value W is higher than the period steady-state threshold, the power generation surplus period of the historical monitoring period is marked as a stable surplus period.

3. A distribution network planning method adapted to the access of new energy sources according to claim 2, characterized in that: The method for obtaining the surplus period ratio Ys is as follows: Extract each column in the power generation surplus schedule as a single column of surplus period, and use the sliding window method to obtain the number of consecutive occurrences of surplus discontinuity periods; Obtain the number of power generation surplus periods in the surplus period column, perform ratio processing on the number of power generation surplus periods and the number of monitoring cycles to obtain the surplus period ratio, and mark the surplus period ratio as Ys; The discontinuity period ratio Jd is obtained by averaging the number of consecutive occurrences of surplus discontinuity periods in the surplus period column to obtain the mean of the discontinuity periods; The intermittent period ratio is obtained by ratio processing the mean value of the intermittent period to the number of monitoring cycles, and the intermittent period ratio is marked as Jd.

4. A distribution network planning method adapted to the access of new energy sources according to claim 1, characterized in that: The method for determining whether the nearest power distribution network can serve as an input access node of the isolated power generation node is as follows: Based on the power topology, the nearest distribution network to the isolated power generation node is obtained, and the nearest distribution network is obtained. Based on the node input model, the adaptive function between the distribution network that reaches the node upper limit value and the nearest distribution network is obtained. ; If the distribution network Lower than the nearest distribution network , the nearest distribution network is used as the input access node of the island generation node.

5. A distribution network planning method adapted to the access of new energy sources according to claim 4, characterized in that: The node input model is constructed as follows: Based on the stable surplus period set, the transmission loss data of the isolated power generation node to the main distribution grid and the nearest distribution subgrid during the stable surplus period is obtained; By formula: Obtain the theoretical loss of three-phase AC power from the island power generation node to the distribution network node ; Where P represents the power generation of the isolated power generation node during the stable surplus period, U is the voltage, represents the power factor, ρ is the resistivity of the transmission line, L is the length of the transmission line, and S is the area of ​​the transmission line; The new energy power input load of the distribution network is processed by ratio with the total power input load in the distribution network to obtain the new energy penetration rate, which is marked as St; Based on the particle swarm optimization algorithm and the theoretical loss of three-phase AC power from the isolated power generation node to the distribution network node , new energy penetration rate, steady-state value W of the period, determine the fitness function , build the node input model.

6. A distribution network planning method adapted to the access of new energy sources according to claim 5, characterized in that: The fitness function The establishment method is: , where β1, β2, and β3 are preset proportional coefficients, Represents the theoretical loss of three-phase AC power in different stable surplus periods , new energy penetration rate, and the maximum value of the steady-state value W during the period.

7. A distribution network planning method adapted to the access of new energy sources according to claim 1, characterized in that: The method for determining whether the stable shortage period of the nearest power distribution network matches the stable surplus period of the isolated power generation node is as follows: By formula: Obtain the time matching degree Pd, where H1 and H2 are the entropies of the stable shortage period set and the stable surplus period set respectively, and max(H1, H2) represents the maximum entropy of the stable shortage period set and the stable surplus period set; If the time matching degree Pd is higher than the time matching degree threshold, the stable shortage period of the nearest distribution network matches the stable surplus period of the island generation node.

8. A distribution network planning method adapted to the access of new energy sources according to claim 7, characterized in that: The entropy H1 of the stable shortage period set and the entropy H2 of the stable surplus period set are obtained as follows: Based on the energy management system of the distribution network, the stable shortage period of the distribution network in all monitoring periods is obtained and stored in the stable shortage period set; Based on the stable shortage period set and the stable surplus period set, the time matching degree is obtained by using the time window and entropy calculation method; Determine the time shear window Δt, divide the monitoring period into multiple time matching windows, and construct the time matching window set S q ={s1, s2, ..., s t }, q is the number of the time matching window set, and the value range of q is [1, t]; Obtain the frequencies f1 and f2 of all time windows including stable shortage periods and stable surplus periods, and obtain the entropies H1 and H2 of the stable shortage period set and stable surplus period set through the information entropy formula.

9. A distribution network planning method adapted to the access of new energy sources according to claim 1, characterized in that: The following steps are also included: Step 5: If the recent stable shortage period of the distribution network does not match the stable surplus period of the isolated power generation node, obtain other distribution network nodes in the power topology map, combine the distribution network node input to the node input model, and determine the input access node of the isolated power generation node.

10. A distribution network planning system adapted to the access of new energy sources, characterized in that: Includes the following modules: Time period collection module: The time period collection module is used to obtain the new energy nodes of isolated power generation in the distribution network, integrate the power generation surplus time periods of the isolated power generation nodes, and build a power generation surplus schedule; Stability analysis module: The stability analysis module is used to perform numerical analysis on the power generation surplus period of the entire monitoring cycle, determine the stable surplus period, and establish a stable surplus time set; Model building module: The model building module is used to build a node input model to determine whether the nearest distribution network can serve as an input access node for the island generation node; Matching judgment module: If the nearest distribution network is used as the input access node of the isolated power generation node, the matching judgment module is used to perform numerical analysis on the power load of the nearest distribution network to determine whether the stable shortage period of the nearest distribution network matches the stable surplus period of the isolated power generation node; Node determination module: If there is no match, the node determination module is used to obtain other distribution network nodes in the power topology diagram, combine the distribution network node input to the node input model, and determine the input access node of the isolated power generation node.

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