Method for determining distributed photovoltaic access strategy of power distribution network based on permeability

Abstract

The invention discloses a method for determining a distributed photovoltaic access strategy of a power distribution network based on permeability. The method comprises the following steps: acquiring permeability information, network topology information and a distributed photovoltaic operation mode of a power distribution network in a preset power supply area; determining a distributed photovoltaic access mode based on the permeability information and the operation mode; based on the permeability information and the network topology information, determining access voltage grade information and access position information of the distributed photovoltaic; and determining a distributed photovoltaic access strategy based on the access mode, the access voltage level information and the access position information. According to the invention, the technical problem that the determination of the distributed photovoltaic access strategy lacks integrity and systematicness in the prior art is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of distribution network, and in particular to a method for determining a distributed photovoltaic access strategy of a distribution network based on penetration rate. Background Art

[0002] As the penetration rate of distributed photovoltaics in distribution networks continues to grow, its impact on network losses, power quality, and safe and stable operation of the power grid is becoming increasingly significant. The problem of distributed photovoltaic access in high-penetration distribution networks is not only related to the economy and efficiency of the power grid, but also directly related to the safety and reliability of the power grid. Although some progress has been made in the existing technology in terms of site selection, capacity determination, and carrying capacity assessment, the following problems still exist:

[0003] (1) The lack of a systematic access system approach has resulted in the separation of key links such as site selection, capacity determination, and carrying capacity assessment, making it difficult to achieve overall optimization;

[0004] (2) Existing capacity assessment methods are mostly based on standardized guidelines, which are difficult to accurately reflect the actual situation and special needs of high-penetration distribution networks.

[0005] To address the above-mentioned problems, no effective solution has been proposed yet. Summary of the invention

[0006] The embodiment of the present invention provides a method for determining a distributed photovoltaic access strategy for a distribution network based on penetration rate, so as to at least solve the technical problem that the determination of the distributed photovoltaic access strategy in the related art lacks integrity and systematicity.

[0007] According to one embodiment of the present invention, a method for determining a distributed photovoltaic access strategy of a distribution network based on permeability is provided, comprising: obtaining permeability information, network topology information and an operating mode of distributed photovoltaics in a preset power supply area; determining an access mode of distributed photovoltaics based on the permeability information and the operating mode; determining access voltage level information and access location information of distributed photovoltaics based on the permeability information and the network topology information; and determining a distributed photovoltaic access strategy based on the access mode, access voltage level information and access location information.

[0008] Optionally, determining the access location information of distributed photovoltaics based on the permeability information and network topology information includes: obtaining the capacity information and expected access quantity of distributed photovoltaics; constructing an objective function based on the capacity information, the expected access quantity and the network topology information; constructing a target constraint relationship set based on the network topology information; setting the target constraint relationship set as the input of a preset search model, searching the objective function, and obtaining candidate solutions, wherein the preset search model is used to represent a model for searching for feasible solutions to the objective function through a particle swarm; and screening candidate solutions based on the permeability information to obtain the access location information.

[0009] Optionally, constructing an objective function based on capacity information, expected access number and network topology information includes: obtaining node actual voltage information, node nominal voltage information, branch current information and branch resistance information in the network topology information; constructing a cost function based on capacity information and expected access number; constructing a voltage deviation function based on node actual voltage information and node nominal voltage information; constructing a distribution network loss function based on branch current information and branch resistance information; and summing the cost function, voltage deviation function and distribution network loss function according to weight coefficients to obtain an objective function.

[0010] Optionally, based on the network topology information, constructing a target constraint relationship set includes: constructing a node voltage constraint relationship based on the actual node voltage information and a preset node voltage threshold; constructing a power flow constraint relationship based on the susceptance information and conductance information in the network topology information; constructing an access capacity constraint relationship based on the photovoltaic capacity information of the network topology information and a preset photovoltaic capacity threshold; constructing an energy storage operation constraint relationship based on the energy storage power in the network topology information and a preset energy storage power threshold.

[0011] Optionally, determining the access voltage level information of distributed photovoltaics based on the penetration information and network topology information includes: obtaining multiple grid strength scores, multiple operating characteristic scores and node load information in the network topology information; determining an adjustment coefficient based on the penetration information, multiple grid strength scores and multiple operating characteristic scores; and determining the access voltage level information based on the adjustment coefficient and load information.

[0012] Optionally, the adjustment coefficient is determined based on the permeability information, multiple grid strength scores and multiple operation characteristic scores: the multiple grid strength scores and multiple operation characteristic scores are weighted using a preset hierarchical analysis model to obtain a weight coefficient; the multiple grid strength scores, multiple operation characteristic scores and the weight coefficient are weighted to obtain a comprehensive score; the preset adjustment coefficient list is searched based on the permeability information and the comprehensive score to obtain the adjustment coefficient.

[0013] Optionally, determining the access mode of distributed photovoltaics based on the penetration rate information and the operation mode includes: obtaining a preset access mode matching table, wherein the penetration rate interval in the preset access mode matching table corresponds to the preset operation mode; searching the preset access mode matching table according to the penetration rate information and the operation mode to obtain the access mode.

[0014] According to one embodiment of the present invention, there is also provided a device for determining a distributed photovoltaic access strategy of a distribution network based on permeability, including: an acquisition module for acquiring permeability information, network topology information and an operation mode of distributed photovoltaics in a preset power supply area; a first determination module for determining the access mode of distributed photovoltaics based on the permeability information and the operation mode; a second determination module for determining the access voltage level information and access location information of distributed photovoltaics based on the permeability information and the network topology information; and a third determination module for determining the distributed photovoltaic access strategy based on the access mode, access voltage level information and access location information.

[0015] Optionally, the acquisition module is also used to obtain capacity information and expected access number of distributed photovoltaics; the device for determining the distributed photovoltaic access strategy of the distribution network based on permeability also includes a construction module, which is used to: construct an objective function based on capacity information, expected access number and network topology information; construct a target constraint relationship set based on network topology information; the second determination module is also used to: set the target constraint relationship set as the input of a preset search model, search the objective function, and obtain candidate solutions, wherein the preset search model is used to represent a model for searching for feasible solutions to the objective function through a particle swarm; and screen candidate solutions according to the permeability information to obtain access location information.

[0016] Optionally, the acquisition module is also used to obtain node actual voltage information, node nominal voltage information, branch current information and branch resistance information in the network topology information; the construction module is also used to: construct a cost function based on capacity information and expected access quantity; construct a voltage deviation function based on node actual voltage information and node nominal voltage information; construct a distribution network loss function based on branch current information and branch resistance information; the second determination module is also used to sum the cost function, voltage deviation function and distribution network loss function according to the weight coefficient to obtain the objective function.

[0017] Optionally, the construction module is also used to: construct a node voltage constraint relationship based on the actual node voltage information and a preset node voltage threshold; construct a power flow constraint relationship based on the susceptance information and conductance information in the network topology information; construct an access capacity constraint relationship based on the photovoltaic capacity information in the network topology information and a preset photovoltaic capacity threshold; construct an energy storage operation constraint relationship based on the energy storage power in the network topology information and a preset energy storage power threshold.

[0018] Optionally, the acquisition module is also used to obtain multiple grid strength scores, multiple operation characteristic scores and node load information in the network topology information; the second determination module is also used to: determine the adjustment coefficient based on the permeability information, multiple grid strength scores and multiple operation characteristic scores; determine the access voltage level information based on the adjustment coefficient and load information.

[0019] Optionally, the second determination module is also used to: use a preset hierarchical analysis model to weight multiple grid strength scores and multiple operating characteristic scores to obtain a weight coefficient; weightedly match multiple grid strength scores, multiple operating characteristic scores and weight coefficients to obtain a comprehensive score; search a preset adjustment coefficient list based on permeability information and the comprehensive score to obtain an adjustment coefficient.

[0020] Optionally, the acquisition module is also used to obtain a preset access mode matching table, wherein the permeability interval in the preset access mode matching table corresponds to the preset operation mode; the first determination module is also used to search the preset access mode matching table based on the permeability information and the operation mode to obtain the access mode.

[0021] According to one embodiment of the present invention, there is also provided an electronic device, comprising: a memory storing an executable program; and a processor for running the program, wherein when the program is running, the method for determining a distributed photovoltaic access strategy for a distribution network based on penetration rate is executed.

[0022] According to one embodiment of the present invention, a computer-readable storage medium is also provided, the computer-readable storage medium including a stored executable program, wherein when the executable program is running, the device where the storage medium is located is controlled to execute the above-mentioned method for determining the distributed photovoltaic access strategy of the distribution network based on penetration rate.

[0023] According to one embodiment of the present invention, a computer program product is also provided, including a computer program, which implements the above-mentioned method for determining a distributed photovoltaic access strategy for a distribution network based on penetration rate when executed by a processor.

[0024] In an embodiment of the present invention, a method is adopted for obtaining the penetration information of the distribution network in a preset power supply area, the network topology information and the operation mode of distributed photovoltaics, and the access mode of distributed photovoltaics is determined based on the penetration information and the operation mode, and the access voltage level information and access location information of distributed photovoltaics are determined based on the penetration information and the network topology information. Finally, the distributed photovoltaic access strategy is determined based on the access mode, the access voltage level information and the access location information, so as to achieve the purpose of comprehensively considering various factors and formulating a scientific and reasonable distributed photovoltaic access strategy, thereby achieving the technical effect of improving the power quality of the power grid, reducing network losses, and ensuring the safe and stable operation of the power grid, and further solving the technical problem of the lack of integrity and systematicity in determining the distributed photovoltaic access strategy in the related technology. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of this application. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0026] Figure 1 It is a hardware structure block diagram of a method for determining a distributed photovoltaic access strategy for a distribution network based on penetration rate according to one embodiment of the present invention;

[0027] Figure 2 is a flow chart of a method for determining a distributed photovoltaic access strategy for a distribution network based on penetration rate according to one embodiment of the present invention;

[0028] Figure 3 is a schematic diagram of a method for determining a distributed photovoltaic access strategy for a distribution network based on penetration rate according to one embodiment of the present invention;

[0029] Figure 4 is a flow chart of another method for determining a distributed photovoltaic access strategy for a distribution network based on penetration rate according to one embodiment of the present invention;

[0030] Figure 5 is a schematic diagram of another method for determining a distributed photovoltaic access strategy for a distribution network based on penetration rate according to one embodiment of the present invention;

[0031] Fig. 6A is a schematic diagram of another method for determining a distributed photovoltaic access strategy for a distribution network based on penetration rate according to one embodiment of the present invention;

[0032] Figure 6B is a schematic diagram of another method for determining a distributed photovoltaic access strategy for a distribution network based on penetration rate according to one embodiment of the present invention;

[0033] Figure 7 is a schematic diagram of another method for determining a distributed photovoltaic access strategy for a distribution network based on penetration rate according to one embodiment of the present invention;

[0034] Figure 8 It is a structural block diagram of a device for determining a distributed photovoltaic access strategy for a distribution network based on penetration rate according to one embodiment of the present invention. DETAILED DESCRIPTION

[0035] 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.

[0036] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0037] The embodiment of the power maintenance order verification method based on multi-view random forest provided in the embodiment of the present application can be executed in a mobile terminal, a computer terminal or a similar computing device. Figure 1 1 is a hardware structure block diagram of a method for determining a distributed photovoltaic access strategy for a distribution network based on penetration rate according to one embodiment of the present invention. Figure 1 As shown, the computer terminal 10 (or electronic device 10) may include one or more (102a, 102b, ..., 102n are used to illustrate) processors (the processor may include but is not limited to a processing device such as a microprocessor MCU or a programmable logic device FPGA), a memory 104 for storing data, and a transmission module 106 for communication functions. In addition, it may also include: a display, an input / output interface (I / O interface), a universal serial bus (USB) port (which may be included as one of the ports of the I / O interface), a network interface, a power supply and / or a camera. It can be understood by those skilled in the art that Figure 1 The structure shown is only for illustration and does not limit the structure of the above electronic device. Figure 1 More or fewer components as shown, or with Figure 1 Different configurations are shown.

[0038] It should be noted that the one or more processors and / or other data processing circuits described above may generally be referred to herein as "data processing circuits". The data processing circuits may be embodied in whole or in part as software, hardware, firmware, or any other combination thereof. In addition, the data processing circuit may be a single independent processing module, or may be incorporated in whole or in part into any of the other components in the computer terminal 10 (or electronic device). As described in the embodiments of the present application, the data processing circuit acts as a processor control (e.g., selection of a variable resistor terminal path connected to an interface).

[0039] The memory 104 can be used to store software programs and modules of application software, such as the program instructions / data storage device corresponding to the method for determining the distributed photovoltaic access strategy of the distribution network based on the penetration rate in the embodiment of the present application. The processor executes various functional applications and data processing by running the software programs and modules stored in the memory 104, that is, the above-mentioned method for determining the distributed photovoltaic access strategy of the distribution network based on the penetration rate is realized. The memory 104 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 104 may further include a memory remotely arranged relative to the processor, and these remote memories may be connected to the computer terminal 10 via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0040] The transmission module 106 is used to receive or send data via a network. The specific example of the above network may include a wireless network provided by a communication provider of the computer terminal 10. In one example, the transmission module 106 includes a network adapter (Network Interface Controller, NIC), which can be connected to other network devices through a base station so as to communicate with the Internet. In one example, the transmission module 106 can be a radio frequency (RF) module, which is used to communicate with the Internet wirelessly.

[0041] The display may be, for example, a touch screen type liquid crystal display (LCD), which may enable a user to interact with a user interface of the computer terminal 10 (or electronic device).

[0042] It should be noted that, in some optional embodiments, the above Figure 1 The computer device (or electronic device) shown may include hardware elements (including circuits), software elements (including computer code stored on a computer-readable medium), or a combination of hardware elements and software elements. It should be noted that Figure 1 This is merely one example of a particular embodiment and is intended to illustrate the types of components that may be present in the above-described computer device (or electronic device).

[0043] According to an embodiment of the present invention, a method embodiment of a method for determining a distributed photovoltaic access strategy for a distribution network based on penetration rate is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in an order different from that shown here.

[0044] Figure 2 is a flow chart of a method for determining a distributed photovoltaic access strategy for a distribution network based on penetration rate according to one embodiment of the present invention, such as Figure 2 As shown, the method comprises the following steps:

[0045] Step S20, obtaining the penetration rate information, network topology information and distributed photovoltaic operation mode of the distribution network in the preset power supply area;

[0046] In step S20, the above penetration rate information is used to characterize the popularity of renewable energy, such as solar photovoltaic (PV) or wind power generation, in the power grid. This indicator is used to measure the proportion of distributed generation resources (DG) in the power system. The higher the penetration rate, the greater the proportion of renewable energy in the power system and the more significant the impact on the power grid.

[0047] The above network topology information is used to characterize the network topology of the distribution network and the parameter information of the devices in the topology, for example, the actual voltage information of the nodes, the distance information between the nodes, the branch current information, the branch voltage information, etc.

[0048] The above-mentioned distributed photovoltaic operation modes include: full grid-connected mode and surplus grid-connected mode. In the full grid-connected mode, all the electricity generated by the distributed photovoltaic power generation system is directly connected to the grid. Users do not directly use this electricity, but sell it to power companies or other users through the grid. In the surplus grid-connected mode, the distributed photovoltaic power generation system first meets the user's own electricity needs (i.e. self-generation and self-use), and the part of the electricity that exceeds the user's needs is connected to the grid. This part of electricity is called surplus electricity.

[0049] Step S22, determining the access mode of distributed photovoltaic based on the penetration information and the operation mode;

[0050] In step S22, the above-mentioned access mode of distributed photovoltaic is used to characterize whether the distributed photovoltaic is connected to the public power grid or the user power grid, and the way of accessing the distribution network.

[0051] Specifically, the preset access mode matching table is searched according to the penetration rate information and the operation mode to obtain the access mode of the distributed photovoltaic.

[0052] Step S24, determining access voltage level information and access location information of distributed photovoltaics based on the penetration rate information and network topology information;

[0053] In step S24, the above-mentioned distributed photovoltaic access voltage level information is used to characterize the voltage level of the grid to which the distributed photovoltaic is connected when it is connected to the distribution network. For example: Low Voltage (LV): usually refers to 220V or 380V AC, which is the standard voltage for ordinary households or small-scale commercial electricity. Medium Voltage (MV): Common medium voltage levels are 10kV, 20kV, 35kV, etc., which are used to transmit electric energy from the high-voltage grid to the low-voltage grid. High Voltage (HV): 110kV, 220kV, etc., used for long-distance power transmission. Ultra High Voltage (UHV): 330kV, 500kV, 750kV, etc., used for ultra-long-distance power transmission.

[0054] The above access location information is used to indicate from which distribution station or distribution room the distributed photovoltaic is connected to the distribution network.

[0055] Specifically, the adjustment coefficient is determined based on the permeability information, multiple grid strength scores and multiple operation characteristic scores; the access voltage level information is determined based on the adjustment coefficient and the node load information in the network topology information.

[0056] Furthermore, an objective function is constructed based on information such as the planned distributed photovoltaic development capacity, the number of distributed photovoltaic developments and network topology information; constraints on the operation of the distribution network are constructed based on the network topology information, and are solved using a preset search model to obtain candidate solutions for the objective function. Finally, candidate solutions are screened based on the penetration rate to determine the access location information.

[0057] Step S26, determining a distributed photovoltaic access strategy based on the access mode, access voltage level information and access location information.

[0058] Specifically, an initial distributed photovoltaic access strategy is formed based on the access mode, access voltage level information and access location information, and after confirmation or adjustment by staff, a final distributed photovoltaic access strategy is obtained.

[0059] Based on the above steps S20 to S26, the penetration information of the distribution network in the preset power supply area, the network topology information and the operation mode of the distributed photovoltaic are obtained, the access mode of the distributed photovoltaic is determined based on the penetration information and the operation mode, and the access voltage level information and access location information of the distributed photovoltaic are determined based on the penetration information and the network topology information. Finally, the distributed photovoltaic access strategy is determined based on the access mode, the access voltage level information and the access location information, so as to achieve the purpose of comprehensively considering various factors and formulating a scientific and reasonable distributed photovoltaic access strategy, thereby achieving the technical effect of improving the power quality of the power grid, reducing network losses, and ensuring the safe and stable operation of the power grid, and further solving the technical problem of the lack of integrity and systematicity in the determination of the distributed photovoltaic access strategy in the related technology.

[0060] Optionally, in step S24, the access location information of distributed photovoltaics determined by using the permeability information and the network topology information includes:

[0061] Step S2411, obtaining capacity information and expected access quantity of distributed photovoltaics;

[0062] In step S2411, the capacity information of the distributed photovoltaic is used to characterize the installed capacity of the distributed photovoltaic to be connected.

[0063] The expected number of distributed photovoltaic access is used to characterize the number of distributed photovoltaic access planned for development. For example, in a distribution network, three distributed photovoltaic projects with an installed capacity of 500kW are planned to be put into operation in a certain year, and the total planned development capacity is 1500kW.

[0064] Step S2412, constructing an objective function based on capacity information, expected access quantity and network topology information;

[0065] Specifically, the cost function is constructed using the capacity information and the expected number of accesses; the voltage deviation function and the distribution network loss function are constructed using the device parameter information in the network topology information.

[0066] Step S2413, constructing a target constraint relationship set based on the network topology information;

[0067] Specifically, the target constraint relationship set is constructed using the device parameter information in the network topology information.

[0068] Step S2414, setting the target constraint relationship set as the input of the preset search model, searching the target function to obtain a candidate solution, wherein the preset search model is used to represent a model for searching a feasible solution of the target function through a particle swarm;

[0069] In step S2414, the preset search model is used to characterize a hybrid genetic algorithm and particle swarm optimization (GA-PSO) algorithm.

[0070] Specifically, the GA-PSO hybrid algorithm effectively combines the advantages of the genetic algorithm and the particle swarm algorithm. It introduces the crossover operation of the genetic algorithm into the particle swarm algorithm to speed up the algorithm solution and improve the solution accuracy. At the same time, the mutation operator is reconstructed to enhance the global convergence ability of the algorithm. The algorithm steps are as follows:

[0071] Step 1: Particle swarm initialization

[0072] Set parameters such as the number of particles, the number of particle digits, and the maximum speed, and randomly generate the position and speed of the initial particles. Generally, the initial particles are uniformly distributed in the space by default, and the initial speed can be set to 0 or a random number. Set genetic algorithm parameters such as crossover probability and mutation probability.

[0073] Step 2: Calculate particle fitness

[0074] The particle fitness is shown in expression (1).

[0075] F=1-G (1)

[0076] Among them, F represents the fitness function and G represents the objective function.

[0077] Step 3: Select an operation

[0078] Assume that the selection probability is P i , the probability P of the i-th particle individual being selected i Its fitness value F i is proportional to, then the probability of selection is P i As shown in expression (2).

[0079]

[0080] Among them, F i represents the fitness value of the i-th particle; N represents the number of particles.

[0081] Step 4: Solve for individual optimality and global optimality

[0082] Initialize the individual optimal p id and the global optimal p gd After that, the global optimal position is determined according to the individual optimal position of the particle after the particle is updated. The update process of the i-th particle at time t+1 is shown in expression (3).

[0083]

[0084] in, represents the position of the i-th particle at time t+1; They represent the position and velocity of the i-th particle at time t respectively; ω represents the inertia weight; represents the individual optimal value of the particle population at time t; represents the global optimal value of the particle population at time t; c1 and c2 represent learning factors, i.e., acceleration constants; r1 and r2 represent random numbers in the range of 0 to 1.

[0085] Step 5: Cross Operation

[0086] Assume that in two individual particles x i 、x j The uniform arithmetic crossover is performed between the two particles, and two new particle individuals are generated after the crossover operation. The crossover process is shown in expression (4).

[0087]

[0088] Among them, x i ′, x′ j represents the i-th and j-th new individuals after the crossover operation; α is a parameter with a value between 0 and 1; x i 、x j Represents the i-th and j-th new individuals before the crossover operation.

[0089] Step 6: Mutation operation

[0090] The velocity variation process of the i-th particle at time t is shown in expression (5).

[0091]

[0092] Among them, v i ' ,t represents the velocity of the i-th particle after mutation at time t; represents the selection probability of the i-th particle individual at time k; represents the selection probability of the i-th particle individual at time k-2.

[0093] The position update process of the i-th particle at time t after individual mutation is shown in expression (6).

[0094]

[0095] in, represents the position of the i-th particle at time t; v i ' ,trepresents the speed of the ith particle after mutation at time t; ω represents the inertia weight; c1 and c2 represent learning factors, i.e., acceleration constants; r1 and r2 represent random numbers in the range of 0 to 1; represents the optimal position of the i-th particle at time t; represents the global optimal position at time t.

[0096] Step 7: Termination condition judgment

[0097] Common termination conditions can be the maximum number of iterations or an acceptable optimal solution. If the termination condition is met, the GA-PSO hybrid algorithm outputs the optimal solution under the current iteration. If the termination condition is not met, Step 2 and subsequent steps are repeated until the termination condition is met.

[0098] Step S2415, screening candidate solutions according to the permeability information to obtain access location information.

[0099] Specifically, when the distributed photovoltaics adopt different aggregation methods, different candidate solutions will be obtained. When the difference between the network loss rate and investment cost between the candidate solutions is less than the preset threshold, the access location information of the distributed photovoltaics is determined in combination with the requirements of the penetration distribution network for power quality.

[0100] Based on the above steps S2411 to S2415, the capacity information and expected access number of distributed photovoltaics are obtained, and the objective function is constructed based on the capacity information, the expected access number and the network topology information. Based on the network topology information, a target constraint relationship set is constructed. Finally, the target constraint relationship set is set as the input of the preset search model, and the objective function is searched to obtain candidate solutions. The candidate solutions are screened according to the permeability information to obtain the access location information. By optimizing the access location, the cost of power grid upgrade and transformation can be reduced and the economy of distributed photovoltaics can be improved. In addition, the GA-PSO hybrid algorithm is used to consider multiple objectives at the same time. By constructing a cost function and a constraint relationship set, multi-objective optimization is achieved, and the purpose of comprehensively considering multiple factors and formulating a scientific and reasonable distributed photovoltaic access strategy is achieved, thereby achieving the technical effect of improving the power quality of the power grid, reducing network losses, and ensuring the safe and stable operation of the power grid, thereby solving the technical problem of lack of integrity and systematicness in determining the distributed photovoltaic access strategy in related technologies.

[0101] Optionally, in step S2412, constructing an objective function based on capacity information, expected access quantity and network topology information includes:

[0102] Step S201, obtaining node actual voltage information, node nominal voltage information, branch current information and branch resistance information in network topology information;

[0103] Step S202, constructing a cost function based on capacity information and expected access quantity;

[0104] Step S203, constructing a voltage deviation function based on the actual node voltage information and the nominal node voltage information;

[0105] Step S204, constructing a distribution network loss function based on the branch current information and the branch resistance information;

[0106] Step S204, performing a sum operation on the cost function, the voltage deviation function and the distribution network loss function according to the weight coefficient to obtain the objective function.

[0107] Specifically, the objective function is shown in expression (7).

[0108]

[0109] Among them, w1+w2+w3=1, w1, w2, w3 are the weights of distributed photovoltaic cost function g1, voltage deviation function g2 and distribution network loss function g3 respectively.

[0110] In the distributed photovoltaic cost function g1: N P represents the expected number of distributed photovoltaic access; r represents the discount rate; m represents the theoretical life of distributed photovoltaic; c1 and c2 represent the construction cost and operation cost of distributed photovoltaic; C pi Represents the installed capacity of the i-th distributed photovoltaic.

[0111] In the voltage deviation function g2, N represents the number of nodes in the distribution network topology; U i Indicates the actual voltage of the ith node in the table; U n represents the nominal voltage of the ith node.

[0112] In the distribution network loss function g3: N b Indicates the number of branches; I j represents the current of the jth branch; R j represents the current in the jth branch.

[0113] Based on the above steps S201 to S204, the actual node voltage information, the nominal node voltage information, the branch current information and the branch resistance information in the network topology information are obtained, and a cost function is constructed based on the capacity information and the expected access quantity, and a voltage deviation function is constructed based on the actual node voltage information and the nominal node voltage information, and a distribution network loss function is constructed based on the branch current information and the branch resistance information. Finally, the cost function, the voltage deviation function and the distribution network loss function are summed according to the weight coefficient to obtain the objective function, which comprehensively considers multiple key factors such as distributed photovoltaic cost, voltage deviation and network loss, can improve the stability and economy of the distributed photovoltaic access strategy, and adjusts the weight coefficient according to different network topology structures and branch characteristics, so as to be suitable for different distribution network environments.

[0114] Optionally, in step S2413, constructing a target constraint relationship set based on the network topology information includes:

[0115] Step S301, constructing a node voltage constraint relationship based on the actual node voltage information and the preset node voltage threshold;

[0116] Specifically, the node voltage constraint relationship indicates that the voltage range of each node is within the allowable voltage upper and lower limits, as shown in expression (8).

[0117] U imin ≤U i ≤U imax (8)

[0118] Among them, U i represents the voltage of node i; U imax Indicates the upper limit of the preset node voltage threshold on the i node, that is, the upper limit of the voltage allowed on the i node; U imin Indicates the lower limit of the preset node voltage threshold on the i-node, that is, the lower limit of the voltage allowed on the i-node.

[0119] Step S302, constructing a power flow constraint relationship based on susceptance information and conductance information in the network topology information;

[0120] Specifically, the power in the distribution network should be balanced, and the power flow constraint relationship is shown in expression (9).

[0121]

[0122] Among them, P i represents the active power of node i; Q i represents the reactive power of node i; U i represents the actual voltage of node i; U j represents the actual voltage of the jth node; G ijrepresents the susceptance between node i and node j; B ij represents the conductance between node i and node j; θ ij Represents the voltage phase angle difference between node i and node j.

[0123] Step S303, constructing an access capacity constraint relationship based on the photovoltaic capacity information of the network topology information and a preset photovoltaic capacity threshold;

[0124] Specifically, the capacity of a single distributed photovoltaic power plant should be less than the maximum capacity that can be connected to the node. If there are multiple nodes connected, the total amount of distributed photovoltaic power plants connected to the node should be less than the maximum capacity that can be connected to the grid. The capacity constraint relationship is shown in expression (10).

[0125]

[0126] Among them, S p,i represents the distributed photovoltaic installed capacity connected to the i-th node; S pm,i represents the preset photovoltaic capacity threshold of the i-th node, which can access the distributed photovoltaic capacity; S pm,max It represents the total distributed photovoltaic capacity that can be connected to all nodes at this voltage level; N represents the sum of the distributed photovoltaic capacity that can be connected to all nodes at this voltage level.

[0127] Step S304: constructing an energy storage operation constraint relationship based on the energy storage power in the network topology information and a preset energy storage power threshold.

[0128] Specifically, power constraints and charge constraints are set for the energy storage in the distribution network to construct the energy storage operation constraint relationship, where the power constraint relationship is used to ensure that the energy storage is within the maximum charging and discharging power range, and the charge constraint relationship is used to avoid overcharging and over-discharging of the energy storage. The power constraint relationship is shown in expression (11).

[0129]

[0130] Among them, P Ci represents the charging power of the i-th energy storage system; P Di represents the discharge power of the i-th energy storage system; P Ci,max represents the maximum charging power of the i-th energy storage system; P Di,max Represents the maximum discharge power of the i-th energy storage system.

[0131] The charge constraint relationship is shown in expression (12).

[0132]

[0133] Among them, SOC i Represents the charge rate of the i-th energy storage system; SOC maxIndicates the maximum charge rate of the energy storage system; SOC min represents the minimum charge rate of the energy storage system; SOC0 represents the initial charge rate of the energy storage system; E i is the capacity of the i-th energy storage system; T represents the number of energy storage systems; P Ci represents the charging power of the i-th energy storage system; P Di represents the discharge power of the i-th energy storage system.

[0134] Based on the above steps S301 to S304, a node voltage constraint relationship is constructed based on the actual node voltage information and the preset node voltage threshold; a power flow constraint relationship is constructed based on the susceptance information and the conductance information in the network topology information; an access capacity constraint relationship is constructed based on the photovoltaic capacity information in the network topology information and the preset photovoltaic capacity threshold; an energy storage operation constraint relationship is constructed based on the energy storage power in the network topology information and the preset energy storage power threshold. Through the target constraint relationship set, the resources in the distribution network can be more reasonably allocated and utilized, and the target constraint relationship set can be adjusted according to the actual operation status and needs of the distribution network, and has strong adaptability and can adapt to changes in the distribution network structure and load fluctuations.

[0135] Optionally, in step S24, determining the access voltage level information of distributed photovoltaic based on the penetration information and the network topology information includes:

[0136] Step S2421, obtaining multiple grid strength scores, multiple operation characteristic scores and node load information in the network topology information;

[0137] In step S2421, the above-mentioned multiple grid strength scores represent the scores corresponding to each influencing factor of grid strength.

[0138] The multiple operation characteristic scores mentioned above represent the scores corresponding to each influencing factor of the operation characteristic.

[0139] The node load information in the above network topology information is used to characterize the daily load information of each node in the distribution network. For example, the load information of each node is obtained at every hour of the day.

[0140] Specifically, Figure 3 is a schematic diagram of a method for determining a distributed photovoltaic access strategy for a distribution network based on penetration rate according to one embodiment of the present invention, such as Figure 3As shown, the figure contains multiple influencing factors of grid strength and multiple influencing factors of operation characteristics. The influencing factors of grid strength are divided into four aspects: grid structure, grid equipment, reliable power supply capacity and automation level. Among them, the grid structure includes: standardized wiring rate, overhead line insulation rate and line cable rate; grid equipment includes: the proportion of old equipment and the typical design application rate of equipment; reliable power supply capacity includes: power supply reliability, N-1 pass rate and substation capacity ratio; automation level includes: automation effective action rate and automation coverage rate. The influencing factors of operation characteristics are divided into three aspects: source, load and storage, power quality, and economic operation. Among them, source, load and storage include: distributed photovoltaic penetration rate, distributed photovoltaic consumption rate, new energy proportion, load rate and energy storage configuration rate; power quality includes: voltage deviation, voltage fluctuation, frequency deviation and harmonic content; economic operation includes: network loss rate and comprehensive line loss rate.

[0141] Step S2422, determining an adjustment coefficient based on the permeability information, a plurality of grid strength scores, and a plurality of operation characteristic scores;

[0142] In step S2422, the above adjustment coefficient is used to determine the maximum carrying capacity of distributed photovoltaics.

[0143] Specifically, a weighted ratio is performed on multiple grid strength scores and multiple operation characteristic scores to obtain a comprehensive score, and the value of the adjustment coefficient is determined based on the comprehensive score and permeability information.

[0144] Step S2423, determining access voltage level information based on the adjustment coefficient and load information.

[0145] Specifically, the technical guidelines for distributed access to the power grid stipulate the principles and requirements for the grid-connected level of distributed photovoltaics, and it is necessary to perform short-circuit current and power quality verification on each voltage level. If the verification fails, the newly connected distributed photovoltaics cannot be carried. If the verification passes, the maximum carrying capacity of distributed photovoltaics needs to be calculated. When the maximum carrying capacity of distributed photovoltaics is greater than the planned development capacity of distributed photovoltaics, the voltage level can meet the distributed photovoltaic access requirements, and when multiple voltage levels are met, the lower voltage level is prioritized for access. Among them, the calculation process of the maximum carrying capacity of distributed photovoltaics is shown in expression (13).

[0146] P m =[S e ×K r -(P D -P L ) max ]×k (13)

[0147] Among them, P m Indicates the maximum carrying capacity of distributed photovoltaics; K rIndicates the operating margin coefficient of distribution network equipment, which is generally 0; S e Indicates the operating limit of the transformer or line; P D The output of the power source connected to the distribution network equipment (including energy storage); P L represents node load information; k represents the adjustment coefficient.

[0148] Furthermore, Table 1 is a table showing the correspondence between the carrying capacity of distributed photovoltaics and the access voltage level. As shown in Table 1, when P m <8kW, the access voltage level is 220V; when 8kW≤P m ≤500kW, the access voltage level is 380V; when 500kW≤P m ≤6000kW, the access voltage level is 10kV; when 6000kW≤P m When the power supply is less than or equal to 10000kW, the access voltage level can be 10(20)kV or 35kV; when the power supply is less than or equal to 10000kW, the access voltage level can be 10(20)kV or 35kV. m When the power is ≤30000kW, the access voltage level can be 10(20)kV, 35Kv, 110kV; 30000kW≤P m ≤100000kW, the access voltage level is 110kV; when P m When the power output is greater than 100000kW, the access voltage level can be 110kV, 220kV, or 500kV.

[0149] Table 1 Correspondence between the carrying capacity of distributed photovoltaic and the access voltage level

[0150] Distributed photovoltaic capacity (kW) Access voltage level <8 220V 8～500 380V 500～6000 10kV 6000～10000 10(20)kV、35kV 10000～30000 10(20)kV、35Kv、110kV 30000～100000 110kV >100000 110kV, 220kV, 500kV

[0151] Based on the above steps S2421 to S2423, a method of obtaining multiple grid strength scores, multiple operation characteristic scores and node load information in the network topology information is adopted, and the adjustment coefficient is determined based on the penetration information, multiple grid strength scores and multiple operation characteristic scores, and the access voltage level information is determined based on the adjustment coefficient and load information. This can ensure that the access of distributed photovoltaics will not have a negative impact on the safe and stable operation of the existing distribution network, balance the access demand of distributed photovoltaics and the carrying capacity of the distribution network, and achieve a reasonable layout and optimal configuration of distributed photovoltaics.

[0152] Optionally, in step S2422, an adjustment coefficient is determined based on the permeability information, a plurality of grid strength scores, and a plurality of operation characteristic scores:

[0153] Step S401, using a preset hierarchical analysis model to weight multiple grid strength scores and multiple operation characteristic scores to obtain a weight coefficient;

[0154] In step S401, the preset analytic hierarchy model is used to characterize the analytic hierarchy process (AHP).

[0155] Specifically, AHP is used to weight multiple grid strength scores and multiple operation characteristic scores to obtain weight coefficients. The criterion layer in AHP is the scores corresponding to each influencing factor of grid strength and the scores corresponding to each influencing factor of operation characteristics. For each element in the criterion layer, a pairwise comparison judgment matrix is ​​constructed. The elements of this matrix are obtained through expert scoring or data analysis, usually using a 1-9 scale, where 1 means that two elements are equally important and 9 means that one element is much more important than another. For the judgment matrix, the eigenvector corresponding to its maximum eigenvalue is calculated, and the eigenvector is the weight coefficient of each element after normalization. In order to ensure the consistency of the judgment matrix, a consistency test is required. The consistency index CI and the random consistency ratio CR are calculated. If CR is less than 0.1, the judgment matrix is ​​considered to have satisfactory consistency. If there are higher-level criteria in the decision problem, the weight coefficient of the lower layer needs to be multiplied by the weight coefficient of the upper layer to obtain the final weight coefficient.

[0156] Step S402, weighting and matching multiple grid strength scores, multiple operation characteristic scores and weight coefficients to obtain a comprehensive score;

[0157] Specifically, each grid strength score and operation characteristic score is multiplied by its corresponding weight coefficient, and then the weighted scores of all scoring dimensions are added together to obtain a comprehensive score.

[0158] Step S403: Search the preset adjustment coefficient list according to the permeability information and the comprehensive score to obtain the adjustment coefficient.

[0159] Table 2 List of preset adjustment coefficients

[0160]

[0161] Specifically, Table 2 is a list of preset adjustment coefficients. As shown in Table 2, when the permeability is greater than 80%, if the comprehensive score is greater than 80, the adjustment coefficient k=0.9, if the comprehensive score is greater than or equal to 70 and less than or equal to 80, the adjustment coefficient k=0.85, if the comprehensive score is less than 70, the adjustment coefficient k=0.7; when the permeability is greater than or equal to 50% and less than or equal to 80%, if the comprehensive score is greater than 80, the adjustment coefficient k=0.95, if the comprehensive score is greater than or equal to 70 and less than or equal to 80, the adjustment coefficient k=0.9, if the comprehensive score is less than 70, the adjustment coefficient k=0.8; when the permeability is less than 50%, if the comprehensive score is greater than 80, the adjustment coefficient k=1, if the comprehensive score is greater than or equal to 70 and less than or equal to 80, the adjustment coefficient k=1, if the comprehensive score is less than 70, the adjustment coefficient k=0.95.

[0162] Based on the above steps S401 to S403, a preset hierarchical analysis model is used to perform weight matching on multiple grid strength scores and multiple operation characteristic scores to obtain a weight coefficient; multiple grid strength scores, multiple operation characteristic scores and weight coefficients are weighted to obtain a comprehensive score; a preset adjustment coefficient list is searched based on the permeability information and the comprehensive score to obtain the adjustment coefficient. The determination of the adjustment coefficient not only depends on the single permeability information, but also combines the comprehensive score, so that the adjustment coefficient can adapt to different engineering conditions and environmental changes, and the hierarchical analysis method is used for weight matching to ensure the scientificity and rationality of the score.

[0163] Optionally, in step S22, determining the access mode of distributed photovoltaic based on the penetration information and the operation mode includes:

[0164] Step S221, obtaining a preset access mode matching table, wherein the penetration rate interval in the preset access mode matching table corresponds to the preset operation mode;

[0165] In step S221, the preset access mode matching table includes the permeation rate value and each permeability interval corresponds to the preset operation mode.

[0166] Step S222: Search the preset access mode matching table according to the penetration rate information and the operation mode to obtain the access mode.

[0167] Specifically, Table 3 is a preset access mode matching table. As shown in Table 3, the table contains the permeability flow rate value and each permeability interval corresponds to the preset operation mode. The preset access mode matching table is searched according to the permeability information and the operation mode to obtain the access mode.

[0168] Table 3 Preset access mode matching table

[0169]

[0170] Specifically, when the penetration rate is less than 15%, that is, in the interval of [0,15%), if the operation mode is full access mode, the access mode is: distributed photovoltaic access to the public grid line; if the operation mode is surplus access mode, the access mode is distributed photovoltaic access to the user grid line. When the penetration rate is greater than or equal to 15% and less than or equal to 50%, that is, in the interval of [15%, 50%), if the operation mode is full access mode, the access mode is: distributed photovoltaic access to the public grid distribution equipment bus; if the operation mode is surplus access mode, the access mode is: distributed photovoltaic access to the user grid distribution equipment bus. When the penetration rate is greater than 50%, that is, in the range of (50%, 100%), if the operation mode is full grid-connected mode, the access mode is: distributed photovoltaic access to the public grid distribution device bus, among which distributed photovoltaics with voltage levels of 10kV and above and capacity of more than 3MW are connected to the public grid distribution device bus through dedicated lines; if the operation mode is surplus grid-connected mode, the access mode is: distributed photovoltaic access to the user's grid equipment bus, among which distributed photovoltaics with voltage levels of 10kV and above are connected to the user's dedicated substation bus.

[0171] Furthermore, the aggregation method of distributed photovoltaics can be determined based on the penetration information. Table 4 is a correspondence table between the aggregation method and the applicable scenario.

[0172] Table 4 Correspondence between collection methods and applicable scenarios

[0173]

[0174] Specifically, as shown in Table 4, when the scenario is that the distributed photovoltaic penetration level of the distribution network is lower than 15%, the number of distributed photovoltaics is small and the overall capacity is not large, the aggregation method is direct parallel aggregation; when the scenario is that the distributed photovoltaic penetration rate in the distribution network is less than 50%, the distributed photovoltaic locations are relatively concentrated, and the overall capacity has a certain scale, the aggregation method is centralized aggregation; when the distributed photovoltaic penetration rate in the distribution network is greater than 50%, the network has abundant flexibility resources and can form a self-consistently operated microgrid, and there are certain requirements for power quality, the aggregation method is microgrid aggregation; when the distributed photovoltaic penetration rate in the distribution network is greater than 50%, large-scale or large distributed photovoltaic systems, higher requirements for power quality, and complex grid structures that require refined management, the aggregation method is multi-level aggregation; when the distributed photovoltaic penetration rate in the grid is greater than 50%, large-scale or large distributed photovoltaic systems, higher requirements for power quality, and advanced interaction with the grid is required, the aggregation method is intelligent aggregation.

[0175] It should be noted that one or more aggregation methods can be selected to determine the access location based on the penetration rate. For example, in a certain scenario, the recommended aggregation method according to the recommended method in Table 4 is centralized aggregation, but since the planned distributed photovoltaic capacity and quantity are not large, decentralized access can also be adopted. For this case, the objective functions of the centralized aggregation and decentralized access schemes can be calculated respectively, and then the final access method can be selected based on the penetration rate information.

[0176] Based on the above steps S221 to S222, a preset access mode matching table is obtained, and the preset access mode matching table is searched according to the penetration rate information and the operation mode to obtain the access mode. Different access modes and aggregation methods can be selected according to different penetration rates and operation modes, thereby providing flexibility for the access of distributed photovoltaics, and by reasonably selecting the access mode, the impact of distributed photovoltaic access on the stability of the power grid can be reduced.

[0177] Figure 4 FIG. 4 is a flow chart of another method for determining a distributed photovoltaic access strategy for a distribution network based on penetration rate according to one embodiment of the present invention. Figure 4 As shown, the method comprises the following steps:

[0178] Step S401, obtaining the penetration rate information, network topology information and distributed photovoltaic operation mode of the distribution network in a preset power supply area;

[0179] Step S402, obtaining a preset access mode matching table;

[0180] Step S403, searching a preset access mode matching table according to the penetration rate information and the operation mode to obtain an access mode;

[0181] Step S404, obtaining capacity information and expected access quantity of distributed photovoltaics;

[0182] Step S405, constructing an objective function based on capacity information, expected access quantity and network topology information;

[0183] Step S406, constructing a target constraint relationship set based on the network topology information;

[0184] Step S407, setting the target constraint relationship set as the input of the preset search model, searching the target function, and obtaining a candidate solution;

[0185] Step S408, screening candidate solutions according to the permeability information to obtain access location information;

[0186] Step S409, obtaining multiple grid strength scores, multiple operation characteristic scores and node load information in the network topology information;

[0187] Step S410, determining an adjustment coefficient based on permeability information, a plurality of grid strength scores, and a plurality of operation characteristic scores;

[0188] Step S411, determining access voltage level information based on the adjustment coefficient and load information;

[0189] Step S412: determining a distributed photovoltaic access strategy based on the access mode, access voltage level information and access location information.

[0190] Based on the above steps S401 to S412, the penetration information of the distribution network in the preset power supply area, the network topology information and the operation mode of the distributed photovoltaic are obtained, the access mode of the distributed photovoltaic is determined based on the penetration information and the operation mode, and the access voltage level information and access location information of the distributed photovoltaic are determined based on the penetration information and the network topology information. Finally, the distributed photovoltaic access strategy is determined based on the access mode, the access voltage level information and the access location information, so as to achieve the purpose of comprehensively considering various factors and formulating a scientific and reasonable distributed photovoltaic access strategy, thereby achieving the technical effect of improving the power quality of the power grid, reducing network losses, and ensuring the safe and stable operation of the power grid, and further solving the technical problem of the lack of integrity and systematicity in determining the distributed photovoltaic access strategy in the relevant technology.

[0191] The following will take the L distribution network line of a city in a certain province as an example to introduce in detail the workflow of the above-mentioned method for determining the distributed photovoltaic access strategy of the distribution network based on penetration rate:

[0192] Assume that the line penetration rate is 23.99%. Currently, there are 3 distributed photovoltaic projects connected to the grid for power generation, with a total capacity of 2500kW. The access points are the #03, #05, and #07 user distribution device buses, and the grid connection level is 10kV. The method for determining the distributed photovoltaic access strategy of the distribution network based on penetration rate is used to output the recommended distributed photovoltaic access strategy for the line. Figure 5 FIG. 1 is a schematic diagram of another method for determining a distributed photovoltaic access strategy for a distribution network based on penetration rate according to one embodiment of the present invention. Figure 5As shown in the figure, the network topology information and related equipment parameters of the distribution network are included. The voltage level of the voltage regulator is clearly marked as 10kV. This means that the distribution network is operated and designed at this voltage level. The distribution network contains a series of substations or distribution stations. #6, #8, #11, #15, #16, and #19 on the line represent nodes in the L distribution network line. #19 indicates whether it is connected to the w line. These nodes are related to the distribution station or distribution room. On the side of the main line, #1, #2, #3, #4, #5, and #6 represent distribution stations, and #7, #8, and #9 represent distribution rooms. The 1600 / 250kVA marked on the #1 distribution station indicates that the transformer capacity is 1600kVA or 250kVA; the 630kVA marked on the #2 distribution station indicates that the transformer capacity is 630kVA; the 630kVA marked on the #7 distribution room indicates that the transformer capacity is 630kVA; the 1000*2kVA marked on the #3 distribution station indicates that there are two transformers with a capacity of 1000kVA, and 1000kW indicates that the photovoltaic installed capacity in the distribution station is 1000kW; the 630kVA marked on the #8 distribution room indicates that the transformer capacity is 630kVA; the 800kVA marked on the #9 distribution room indicates that the transformer capacity is 1000kW. VA means the transformer capacity is 800kVA; 630*3kVA marked on the #5 substation means there are 3 transformers with a transformer capacity of 630kVA, and 1000kW means the photovoltaic installed capacity in the substation is 1000kW; 630*3kVA marked on the #6 substation means there are 3 transformers with a transformer capacity of 630kVA, and 500kW means the photovoltaic installed capacity in the substation is 500kW; 800*2kVA marked on the #4 substation means there are 2 transformers with a transformer capacity of 800kVA, and 1000kW means the maximum power that the substation can provide is 1000kW. In addition, Figure 5 The marked YJV22-3*300 and LGJ-240 indicate the material of the cable, etc. At the same time, the length information of each cable is also listed in detail. For example, the marked LGJ-240 and 0.295km between node #11 and node #15 indicates that #11 and #15 are connected by LGJ-240 cable, and the cable length is 0.295km.

[0193] Assume that the line plans to put into operation three distributed photovoltaic projects with an installed capacity of 500kW, with a total planned development capacity of 1500kW. It belongs to user investment and construction, and the operation mode is self-use, and the surplus is connected to the grid. Referring to Table 3 and Table 4, it is recommended that the distributed photovoltaic power generation planned for this line be connected to the busbar of the user's power distribution device, and the recommended collection method is centralized collection and access. Since the planned distributed photovoltaic capacity and quantity are not large, the centralized collection and access method may not be adopted. According to the principle of distributed photovoltaic access technology, if the planned distributed photovoltaic is centralized accessed at one point by the collection method, the total capacity of 1500kW can be connected to 10kV according to Table 1. If the planned distributed photovoltaic is decentralized, each distributed photovoltaic capacity of 500kW can be connected to 10kV or 380V according to Table 1. The comprehensive score of the grid strength and operation characteristics of the distribution network unit where the line is located is 73.47 points. The adjustment parameters refer to Table 2 and take k=1.

[0194] Fig. 6A FIG. 1 is a schematic diagram of another method for determining a distributed photovoltaic access strategy for a distribution network based on penetration rate according to one embodiment of the present invention. Fig. 6A As shown, the figure shows the daily load information of distribution stations #1, #2, #3, #4, #5, #6 and distribution rooms #7, #8, #9. Figure 6B FIG. 1 is a schematic diagram of another method for determining a distributed photovoltaic access strategy for a distribution network based on penetration rate according to one embodiment of the present invention. Figure 6B As shown in the figure, the distributed photovoltaic output of the busbars of the user distribution devices connected to the distribution stations #3, #5, and #6 is shown. Fig. 6A , Figure 6B And expression (13), calculate the maximum carrying capacity of distributed photovoltaic power distribution equipment of each user at the voltage level of 10kV and 0.4kV. As shown in Table 5, Table 5 shows the maximum carrying capacity of distributed photovoltaic power distribution equipment of each user at the voltage level of 10kV and 0.4kV.

[0195] As shown in Table 5, if distributed photovoltaics adopt decentralized access, the maximum load capacity of the distributed photovoltaic access of the distribution equipment bus at the 0.4kV voltage level is less than 500kW, which cannot meet the access requirements, while the 9 distribution equipment buses at the 10kV voltage level can meet the access requirements. If distributed photovoltaics adopt centralized access after being collected, only the #1 to #5 distribution equipment buses at the 10kV voltage level can meet the access requirements. On the whole, it is recommended that distributed photovoltaics be connected to the 10kV voltage level.

[0196] According to the penetration rate and network topology information of line L, the objective function of the distributed photovoltaic access location is constructed according to expression (7), and the target constraint relationship set of the distributed photovoltaic access location is constructed according to (8)-(12). Among them, the planned distributed photovoltaic capacity is 500kW and the number is 3. The initial population of the GA-PSO algorithm is set to 300, the number of iterations is 50, the learning factor is 2, α is 0.7, and the mutation probability is 0.5. Figure 7 is a schematic diagram of another method for determining a distributed photovoltaic access strategy for a distribution network based on penetration rate according to one embodiment of the present invention, such as Figure 7 As shown in the figure, during the iteration process, the objective function of the distributed photovoltaic centralized access scheme tends to be stable after the 8th iteration, and the distributed photovoltaic decentralized access scheme tends to be stable after the 14th iteration. Therefore, the result of the objective function of the distributed photovoltaic centralized access scheme at the 8th iteration is taken as the candidate solution, and the result of the distributed photovoltaic decentralized access scheme at the 14th iteration is taken as the candidate solution.

[0197] Table 5 Maximum distributed photovoltaic load capacity of each user's distribution equipment at 10kV and 0.4kV voltage levels

[0198]

[0199] Table 6 Solution results of GA-PSO hybrid algorithm for distributed photovoltaic centralized access scheme and decentralized access scheme

[0200]

[0201] Specifically, Table 6 shows the optimization results of the GA-PSO hybrid algorithm for the centralized access scheme and the decentralized access scheme of distributed photovoltaics. As shown in Table 6, the decentralized access scheme can effectively reduce the network loss rate, but the superposition of multiple inverters will lead to an increase in voltage deviation, that is, an increase in the adverse impact on power quality. The centralized access scheme can reduce the adverse impact of the inverter on power quality, but the network loss rate increases, and a special collection box equipment needs to be built. Therefore, the average annual investment cost of distributed photovoltaics considering the discount rate and the theoretical life of distributed photovoltaics increases. In the case that the network loss rate and investment cost are not much different, considering the high requirements of the distribution network penetration rate on power quality and the subsequent intelligent development of the distribution network, it is recommended that the distributed photovoltaics with a total capacity of 1500kW planned to be developed in the future be decentralized and connected to the 10kV side bus of #4, #5, and #9 distribution. Therefore, the recommended access scheme for the three distributed photovoltaics with a capacity of 500kW planned to be developed on the L line is to recommend decentralized access to the 10kV side bus of #4, #5, and #9 user distribution equipment.

[0202] Based on the above embodiments, the penetration rate information, network topology information and operation mode of distributed photovoltaics in the preset power supply area are obtained, the access mode of distributed photovoltaics is determined based on the penetration rate information and the operation mode, and the access voltage level information and access location information of distributed photovoltaics are determined based on the penetration rate information and the network topology information. Finally, the distributed photovoltaic access strategy is determined based on the access mode, access voltage level information and access location information, so as to achieve the purpose of comprehensively considering various factors and formulating a scientific and reasonable distributed photovoltaic access strategy, thereby achieving the technical effect of improving the power quality of the power grid, reducing network losses, and ensuring the safe and stable operation of the power grid, and further solving the technical problem of the lack of integrity and systematicity in the determination of distributed photovoltaic access strategies in related technologies.

[0203] Through the description of the above implementation methods, those skilled in the art can clearly understand that the method according to the above embodiment can be implemented by means of software plus a necessary general hardware platform, 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, which is stored in a storage medium (such as ROM / RAM, a magnetic disk, or an optical disk), and includes a number of instructions for a terminal device (which can be a mobile phone, a computer, a server, or a network device, etc.) to execute the methods of various embodiments of the present invention.

[0204] In an embodiment of the present invention, a device for determining a distributed photovoltaic access strategy for a distribution network based on penetration is also provided, and the device is used to implement the above-mentioned embodiments and preferred implementation modes, and the descriptions that have been made will not be repeated. As used below, the term "module" can implement a combination of software and / or hardware for a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceivable.

[0205] Figure 8 is a structural block diagram of a device for determining a distributed photovoltaic access strategy for a distribution network based on penetration rate according to one embodiment of the present invention, such as Figure 8 As shown, the device comprises:

[0206] An acquisition module 801 is used to acquire the penetration rate information, network topology information and distributed photovoltaic operation mode of the distribution network in a preset power supply area;

[0207] A first determination module 802 is used to determine the access mode of distributed photovoltaic based on the penetration rate information and the operation mode;

[0208] The second determination module 803 is used to determine the access voltage level information and access location information of the distributed photovoltaic based on the permeability information and the network topology information;

[0209] The third determination module 804 is used to determine the distributed photovoltaic access strategy based on the access mode, access voltage level information and access location information.

[0210] Optionally, the acquisition module 801 is also used to obtain capacity information and expected access number of distributed photovoltaics; the device for determining the distributed photovoltaic access strategy of the distribution network based on permeability also includes a construction module 805, which is used to: construct an objective function based on capacity information, expected access number and network topology information; construct a target constraint relationship set based on network topology information; the second determination module 803 is also used to: set the target constraint relationship set as the input of a preset search model, search the objective function, and obtain candidate solutions, wherein the preset search model is used to represent a model for searching for feasible solutions to the objective function through a particle swarm; filter candidate solutions according to permeability information to obtain access location information.

[0211] Optionally, the acquisition module 801 is also used to obtain the actual node voltage information, the nominal node voltage information, the branch current information and the branch resistance information in the network topology information; the construction module 805 is also used to: construct a cost function based on the capacity information and the expected number of accesses; construct a voltage deviation function based on the actual node voltage information and the nominal node voltage information; construct a distribution network loss function based on the branch current information and the branch resistance information; the second determination module 803 is also used to sum the cost function, the voltage deviation function and the distribution network loss function according to the weight coefficient to obtain the objective function.

[0212] Optionally, the construction module 805 is also used to: construct a node voltage constraint relationship based on the actual node voltage information and the preset node voltage threshold; construct a power flow constraint relationship based on the susceptance information and conductance information in the network topology information; construct an access capacity constraint relationship based on the photovoltaic capacity information of the network topology information and the preset photovoltaic capacity threshold; construct an energy storage operation constraint relationship based on the energy storage power in the network topology information and the preset energy storage power threshold.

[0213] Optionally, the acquisition module 801 is also used to obtain multiple grid strength scores, multiple operation characteristic scores and node load information in the network topology information; the second determination module 803 is also used to: determine the adjustment coefficient based on the permeability information, multiple grid strength scores and multiple operation characteristic scores; determine the access voltage level information based on the adjustment coefficient and load information.

[0214] Optionally, the second determination module 803 is also used to: use a preset hierarchical analysis model to weight multiple grid strength scores and multiple operation characteristic scores to obtain a weight coefficient; weightedly match multiple grid strength scores, multiple operation characteristic scores and weight coefficients to obtain a comprehensive score; search a preset adjustment coefficient list based on permeability information and the comprehensive score to obtain an adjustment coefficient.

[0215] Optionally, the acquisition module 801 is also used to obtain a preset access mode matching table, wherein the permeability interval in the preset access mode matching table corresponds to the preset operation mode; the first determination module 802 is also used to search the preset access mode matching table based on the permeability information and the operation mode to obtain the access mode.

[0216] It should be noted that the above modules can be implemented by software or hardware. For the latter, it can be implemented in the following ways, but not limited to: the above modules are all located in the same processor; or the above modules are located in different processors in any combination.

[0217] According to one embodiment of the present invention, there is also provided an electronic device, comprising: a memory storing an executable program; and a processor for running the program, wherein when the program is running, the method for determining a distributed photovoltaic access strategy for a distribution network based on penetration rate is executed.

[0218] Optionally, in this embodiment, the processor may be configured to perform the following steps through a computer program:

[0219] Step S1, obtaining the penetration rate information, network topology information and distributed photovoltaic operation mode of the distribution network in a preset power supply area;

[0220] Step S2, determining the access mode of distributed photovoltaic based on the penetration information and the operation mode;

[0221] Step S3, determining access voltage level information and access location information of distributed photovoltaics based on the penetration rate information and network topology information;

[0222] Step S4, determining a distributed photovoltaic access strategy based on the access mode, access voltage level information and access location information.

[0223] According to one embodiment of the present invention, a computer-readable storage medium is also provided, the computer-readable storage medium including a stored executable program, wherein when the executable program is running, the device where the storage medium is located is controlled to execute the above-mentioned method for determining the distributed photovoltaic access strategy of the distribution network based on penetration rate.

[0224] Optionally, in this embodiment, the storage medium may be configured to store a computer program for performing the following steps:

[0225] Step S1, obtaining the penetration rate information, network topology information and distributed photovoltaic operation mode of the distribution network in a preset power supply area;

[0226] Step S2, determining the access mode of distributed photovoltaic based on the penetration information and the operation mode;

[0227] Step S3, determining access voltage level information and access location information of distributed photovoltaics based on the penetration rate information and network topology information;

[0228] Step S4, determining a distributed photovoltaic access strategy based on the access mode, access voltage level information and access location information.

[0229] Optionally, in this embodiment, the above-mentioned storage medium may include but is not limited to: a USB flash drive, a read-only memory (ROM), a random access memory (RAM), a mobile hard disk, a magnetic disk or an optical disk, and other media that can store computer programs.

[0230] According to one embodiment of the present invention, a computer program product is also provided, including a computer program, which implements the above-mentioned method for determining a distributed photovoltaic access strategy for a distribution network based on penetration rate when executed by a processor.

[0231] Optionally, in this embodiment, the computer program product may be configured to store computer program instructions for performing the following steps:

[0232] Step S1, obtaining the penetration rate information, network topology information and distributed photovoltaic operation mode of the distribution network in a preset power supply area;

[0233] Step S2, determining the access mode of distributed photovoltaic based on the penetration information and the operation mode;

[0234] Step S3, determining access voltage level information and access location information of distributed photovoltaics based on the penetration rate information and network topology information;

[0235] Step S4, determining a distributed photovoltaic access strategy based on the access mode, access voltage level information and access location information.

[0236] Optionally, the specific examples in this embodiment may refer to the examples described in the above embodiments and optional implementation modes, and this embodiment will not be described in detail here.

[0237] The serial numbers of the above embodiments of the present invention are only for description and do not represent the advantages or disadvantages of the embodiments.

[0238] In the above embodiments of the present invention, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0239] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only schematic. For example, the division of the units can be a logical function division. There may be other division methods in actual implementation. For example, 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 units or modules, which can be electrical or other forms.

[0240] 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 units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0241] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0242] 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 technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, magnetic disk or optical disk and other media that can store program codes.

[0243] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for determining a distributed photovoltaic access strategy for a distribution network based on penetration, characterized in that: include: Obtain the penetration rate information, network topology information and distributed photovoltaic operation mode of the distribution network in the preset power supply area; Determining an access mode of the distributed photovoltaic system based on the penetration rate information and the operation mode; Determine the access voltage level information and access location information of the distributed photovoltaic based on the permeability information and the network topology information; The distributed photovoltaic access strategy is determined based on the access mode, the access voltage level information and the access location information.

2. The method for determining the distributed photovoltaic access strategy of the distribution network based on penetration rate according to claim 1 is characterized in that: The access location information of the distributed photovoltaic determined by the permeability information and the network topology information includes: Obtaining the capacity information and expected access quantity of the distributed photovoltaic system; Constructing an objective function based on the capacity information, the expected number of accesses, and the network topology information; Based on the network topology information, construct a target constraint relationship set; The target constraint relationship set is set as the input of a preset search model, and the target function is searched to obtain a candidate solution, wherein the preset search model is used to represent a model for searching a feasible solution of the target function through a particle swarm; The candidate solutions are screened according to the permeability information to obtain the access location information.

3. The method for determining the distributed photovoltaic access strategy of the distribution network based on penetration rate according to claim 2 is characterized in that: Constructing an objective function based on the capacity information, the expected number of accesses, and the network topology information includes: Acquire node actual voltage information, node nominal voltage information, branch current information, and branch resistance information in the network topology information; construct a cost function based on the capacity information and the expected number of accesses; Constructing a voltage deviation function based on the actual voltage information of the node and the nominal voltage information of the node; Based on the branch current information and the branch resistance information, construct a distribution network loss function; The cost function, the voltage deviation function and the distribution network loss function are summed according to the weight coefficient to obtain the objective function.

4. The method for determining the distributed photovoltaic access strategy of the distribution network based on penetration rate according to claim 3 is characterized in that: Based on the network topology information, constructing the target constraint relationship set includes: Constructing a node voltage constraint relationship based on the node actual voltage information and a preset node voltage threshold; Based on the susceptance information and conductance information in the network topology information, construct a power flow constraint relationship; Based on the photovoltaic capacity information of the network topology information and a preset photovoltaic capacity threshold, constructing an access capacity constraint relationship; Based on the energy storage power in the network topology information and a preset energy storage power threshold, an energy storage operation constraint relationship is established.

5. The method for determining the distributed photovoltaic access strategy of the distribution network based on penetration rate according to claim 2 is characterized in that: Determining the access voltage level information of the distributed photovoltaic based on the penetration rate information and the network topology information includes: Obtaining a plurality of grid strength scores, a plurality of operation characteristic scores, and node load information in the network topology information; determining an adjustment factor based on the permeability information, the plurality of grid strength scores, and the plurality of operational characteristic scores; The access voltage level information is determined based on the adjustment coefficient and the load information.

6. The method for determining the distributed photovoltaic access strategy of the distribution network based on penetration rate according to claim 5 is characterized in that: Determine an adjustment factor based on the permeability information, the plurality of grid strength scores, and the plurality of operation characteristic scores: Using a preset hierarchical analysis model, weighting the multiple grid strength scores and the multiple operation characteristic scores is performed to obtain a weight coefficient; Performing weighted matching on the multiple grid strength scores, the multiple operation characteristic scores, and the weight coefficients to obtain a comprehensive score; The preset adjustment coefficient list is searched according to the permeability information and the comprehensive score to obtain the adjustment coefficient.

7. The method for determining the distributed photovoltaic access strategy of the distribution network based on penetration rate according to claim 2 is characterized in that: Determining the access mode of the distributed photovoltaic based on the penetration rate information and the operation mode includes: Obtaining a preset access mode matching table, wherein the penetration rate interval in the preset access mode matching table corresponds to the preset operation mode; The preset access mode matching table is searched according to the penetration rate information and the operation mode to obtain the access mode.

8. An electronic device, characterized in that: include: A memory storing an executable program; A processor is used to run the program, wherein when the program is running, the method for determining the distributed photovoltaic access strategy of the distribution network based on penetration rate as described in any one of claims 1 to 7 is executed.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored executable program, wherein when the executable program is running, the device where the storage medium is located is controlled to execute the method for determining a distributed photovoltaic access strategy for a distribution network based on penetration rate as described in any one of claims 1 to 7.

10. A computer program product, characterized in that It comprises a computer program, which, when executed by a processor, implements the method for determining a distributed photovoltaic access strategy for a distribution network based on penetration rate according to any one of claims 1 to 7.

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